vis_results.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import argparse\n",
    "import json\n",
    "import os\n",
    "from glob import glob\n",
    "from os.path import join as pjoin\n",
    "\n",
    "import gurobi_logtools as glt\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from scipy import interpolate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Relative primal gap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Exp_result:\n",
    "    def __init__(self, test_logs_dir, TaskName, solver, exp_id, search, name, color, marker):\n",
    "        self.result_dir = pjoin(test_logs_dir, TaskName, exp_id, solver, search)\n",
    "        self.exp_id = exp_id\n",
    "        self.search = search\n",
    "        self.name = name\n",
    "        self.color = color\n",
    "        self.marker = marker\n",
    "        self.n_infeasible = 0\n",
    "        self.min_ys = []\n",
    "        self.ys = []\n",
    "        self.integrals = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_x_y(file, p_bound, x_lim):\n",
    "    result = glt.parse(file)\n",
    "    nodelog_progress = result.progress(\"nodelog\")\n",
    "    if len(nodelog_progress) <= 1:\n",
    "        return None, None\n",
    "    nodelog_progress = nodelog_progress[[\"Incumbent\", \"Time\"]].dropna()\n",
    "    new_row = pd.DataFrame({'Incumbent': [p_bound], 'Time': [0]})\n",
    "    df = pd.concat([new_row, nodelog_progress]).reset_index(drop=True)\n",
    "    \n",
    "    x = df[\"Time\"].to_list()\n",
    "    y = df[\"Incumbent\"].to_list()\n",
    "    \n",
    "    xnew = np.arange(0, x_lim, 1)\n",
    "    ynew = np.interp(xnew, x, y)\n",
    "    min_y = np.min(y)\n",
    "    \n",
    "    df.drop_duplicates(['Time'], keep='last', inplace=True)\n",
    "    df[\"dt\"] = np.array(df[\"Time\"].to_list()[1:] + [x_lim]) - df[\"Time\"]\n",
    "    df['area'] = df['Incumbent'] * df['dt']\n",
    "    integral = df['area'].sum()\n",
    "    \n",
    "    return list(ynew), min_y, integral"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_lim = 1000\n",
    "TaskName = \"IP\"\n",
    "solver = \"GRB\"\n",
    "# exp_list = [\n",
    "#     [\"240812-035802\", \"400_5_1\", \"PAS\", \"green\", \"-\"],\n",
    "#     [\"240812-141737\", \"100_5_15\", \"Ours\", \"orange\", \"-\"]\n",
    "# ]\n",
    "exp_list = [\n",
    "    [\"240831-162652\", \"100_5_15\", \"emb\", \"red\", \"-\"],\n",
    "    [\"240831-203523\", \"100_5_15\", \"uniform\", \"green\", \":\"],\n",
    "    [\"240831-162625\", \"100_5_15\", \"normal\", \"orange\", \":\"],\n",
    "    [\"240831-162631\", \"100_5_15\", \"uniform_h\", \"green\", \"-\"],\n",
    "    [\"240831-162646\", \"100_5_15\", \"normal_h\", \"orange\", \"-\"],\n",
    "    [\"240831-165318\", \"100_5_15\", \"uniform_h2\", \"green\", \"-\"],\n",
    "    [\"240831-165325\", \"100_5_15\", \"normal_h2\", \"orange\", \"-\"],\n",
    "    # [\"240830-145728\", \"100_5_15\", \"xavier_uniform\", \"orange\", \"--\"],\n",
    "    # [\"240829-223837\", \"100_5_15\", \"xavier_normal\", \"green\", \"--\"],\n",
    "    # [\"240830-200428\", \"100_5_15\", \"kaiming_uniform\", \"orange\", \"-\"],\n",
    "    # [\"240830-192414\", \"100_5_15\", \"kaiming_normal\", \"green\", \"-\"],\n",
    "    # [\"240830-150012\", \"100_5_15\", \"kaiming_normal_4\", \"blue\", \"-\"],\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = \"/mnt/disk1/thlee/MILP/pas/\"\n",
    "gt_logs_dir = pjoin(base_dir, \"dataset\")\n",
    "test_logs_dir = pjoin(base_dir, \"test_logs\")\n",
    "ins_dir = pjoin(base_dir, f\"instance/{TaskName}/test\")\n",
    "grb_dir = pjoin(gt_logs_dir, TaskName, \"test/logs\")\n",
    "\n",
    "ins_names = sorted(os.listdir(grb_dir))\n",
    "ins_names = [ins.split(\".\")[0] for ins in ins_names]\n",
    "\n",
    "exp_results = {exp_info[2]: Exp_result(test_logs_dir, TaskName, solver, *exp_info) for exp_info in exp_list}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "feasible_ins, ins_bks, ys_grb, min_ys_grb, integrals_grb = [], [], [], [], []\n",
    "n_infeasible = 0\n",
    "for ins in ins_names:\n",
    "    ins_json = pjoin(ins_dir, f\"{ins}.json\")\n",
    "    ins_grb = pjoin(grb_dir, f\"{ins}.mps.gz.log\")\n",
    "\n",
    "    with open(ins_json, \"r\") as file:\n",
    "        data = json.load(file)\n",
    "    p_bound = data[\"primal_bound\"]\n",
    "    y_grb, min_y_grb, integral_grb = get_x_y(ins_grb, p_bound, x_lim)\n",
    "    \n",
    "    is_infeasible = False\n",
    "    for exp in exp_results.values():\n",
    "        ins_path = pjoin(exp.result_dir, f\"{ins}.log\")\n",
    "        exp.y, exp.min_y, exp.integral = get_x_y(ins_path, p_bound, x_lim)\n",
    "        if exp.y is None:\n",
    "            is_infeasible = True\n",
    "            exp.n_infeasible += 1\n",
    "            \n",
    "    if is_infeasible:\n",
    "        n_infeasible += 1\n",
    "        continue\n",
    "    \n",
    "    ys_grb.append(y_grb)\n",
    "    feasible_ins.append(ins)\n",
    "    min_ys_grb.append(min_y_grb)\n",
    "    integrals_grb.append(integral_grb)\n",
    "    \n",
    "    min_ys = []\n",
    "    for exp in exp_results.values():\n",
    "        exp.min_ys.append(exp.min_y)\n",
    "        exp.ys.append(exp.y)\n",
    "        exp.integrals.append(exp.integral)\n",
    "        min_ys.append(exp.min_y)\n",
    "    ins_bks.append(np.min([min_y_grb] + min_ys))\n",
    "    \n",
    "min_ys_grb = np.array(min_ys_grb)\n",
    "ys_grb = np.array(ys_grb)\n",
    "ins_bks = np.array(ins_bks).reshape([-1, 1])\n",
    "integrals_grb = np.array(integrals_grb).reshape([-1, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "integral of gurobi: 2408.5\n",
      "integral of emb: 1810.6\n",
      "integral of uniform: 1219.5\n",
      "integral of normal: 1385.1\n",
      "integral of uniform_h: 1408.1\n",
      "integral of normal_h: 1293.4\n",
      "integral of uniform_h2: 1539.7\n",
      "integral of normal_h2: 1444.1\n",
      "Total number of infeasible instances: 0\n",
      "number of infeasible of emb: 0\n",
      "number of infeasible of uniform: 0\n",
      "number of infeasible of normal: 0\n",
      "number of infeasible of uniform_h: 0\n",
      "number of infeasible of normal_h: 0\n",
      "number of infeasible of uniform_h2: 0\n",
      "number of infeasible of normal_h2: 0\n"
     ]
    }
   ],
   "source": [
    "integrals_grb = integrals_grb - (ins_bks * x_lim)\n",
    "print(f\"integral of gurobi: {integrals_grb.mean():.1f}\")\n",
    "\n",
    "for exp in exp_results.values():\n",
    "    exp.min_ys = np.array(exp.min_ys)\n",
    "    exp.ys = np.array(exp.ys)\n",
    "    exp.integrals = np.array(exp.integrals).reshape([-1, 1])\n",
    "    exp.integrals = exp.integrals - (ins_bks * x_lim)\n",
    "    print(f\"integral of {exp.name}: {exp.integrals.mean():.1f}\")\n",
    "\n",
    "print(f\"Total number of infeasible instances: {n_infeasible}\")\n",
    "r_gap_grb = np.abs(ys_grb - ins_bks) / np.abs(ins_bks)\n",
    "mean_grb = r_gap_grb.mean(axis=0)\n",
    "std_grb = r_gap_grb.std(axis=0)\n",
    "\n",
    "\n",
    "for exp in exp_results.values():\n",
    "    exp.r_gap = np.abs(exp.ys - ins_bks) / np.abs(ins_bks)\n",
    "    exp.mean = exp.r_gap.mean(axis=0)\n",
    "    exp.std = exp.r_gap.std(axis=0)\n",
    "    print(f\"number of infeasible of {exp.name}: {exp.n_infeasible}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 10))\n",
    "xnew = np.arange(1, x_lim+1, 1)\n",
    "# plt.plot(xnew, mean_grb, \"-\", label=\"Gurobi\", color=\"gray\")\n",
    "# plt.fill_between(xnew, ys_grb - std_grb, ys_grb + std_grb, alpha=0.2)\n",
    "\n",
    "for exp in exp_results.values():\n",
    "    plt.plot(xnew, exp.mean, exp.marker, label=exp.name, color=exp.color)\n",
    "    # plt.fill_between(xnew, exp.ys - exp.std, exp.ys + exp.std, alpha=0.2)\n",
    "\n",
    "# plt.xlim((10, 1000))\n",
    "# plt.xlim((1, 600))\n",
    "plt.xscale(\"log\")\n",
    "plt.yscale(\"log\")\n",
    "plt.xlabel(\"time (sec)\", fontsize=13)\n",
    "plt.ylabel(\"Relative primal gap\", fontsize=13)\n",
    "# plt.title(f\"{par}_{d_type}\")\n",
    "plt.legend(fontsize=13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ins_name = np.array([int(ins.split(\"_\")[-1]) for ins in feasible_ins]) - 10000\n",
    "x = np.arange(len(ins_name))  # x locations for the groups\n",
    "\n",
    "ys_grb = min_ys_grb - min_ys_grb\n",
    "ys = exp_results[\"Ours\"].min_ys - min_ys_grb\n",
    "\n",
    "plt.figure(figsize=(16, 6))\n",
    "plt.bar(x, ys, width=0.5, label=\"Ours+Gurobi (10min)\", color=\"navy\")\n",
    "plt.plot(x, np.zeros(len(ys)), \"--\", label=\"Gurobi (60min)\", color=\"orange\", linewidth=3.5)\n",
    "plt.xlabel(\"Instances\", fontsize=15)\n",
    "plt.ylabel(\"Primal gaps\", fontsize=15)\n",
    "# plt.title('Bar chart with standard deviation')\n",
    "plt.xticks(x, ins_name, rotation=90, fontsize=10)\n",
    "plt.legend(fontsize=12)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "for par in params:\n",
    "    ys_dict[par] = {}\n",
    "    for d_type in datatypes:\n",
    "        dir_path = os.path.join(base_dir, par, d_type)\n",
    "        ys_dict[par][d_type] = get_x_y(dir_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [],
   "source": [
    "gurobi_train_path = \"/mnt/disk1/thlee/MILP/pas/dataset/CJ/train/logs\"\n",
    "gurobi_val_path = \"/mnt/disk1/thlee/MILP/pas/dataset/CJ/val/logs\"\n",
    "xnew = np.arange(1, 600, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_y = get_x_y(gurobi_train_path)\n",
    "val_y = get_x_y(gurobi_val_path)\n",
    "y = {}\n",
    "y[\"train\"] = train_y\n",
    "y[\"val\"] = val_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xnew, train_y, \"-\", label=\"train_y\")\n",
    "plt.plot(xnew, val_y, \"-\", label=\"val_y\")\n",
    "plt.xscale(\"log\")\n",
    "plt.xlabel(\"time (sec)\")\n",
    "plt.ylabel(\"Incumbent solution’s objective value\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for par in params:\n",
    "    for d_type in datatypes:\n",
    "        plt.plot(xnew, y[d_type], \"-\", label=\"Gurobi\")\n",
    "        plt.plot(xnew, ys_dict[par][d_type], \"-\", label=\"PS+Gurobi\")\n",
    "        plt.xscale(\"log\")\n",
    "        plt.yscale(\"log\")\n",
    "        plt.xlabel(\"time (sec)\")\n",
    "        plt.ylabel(\"Incumbent solution’s objective value\")\n",
    "        plt.title(f\"{par}_{d_type}\")\n",
    "        plt.legend()\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# histogram of each variable's value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import io\n",
    "import os\n",
    "import pickle\n",
    "from glob import glob\n",
    "\n",
    "import gurobipy as gp\n",
    "import numpy as np\n",
    "import torchimport torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CPU_Unpickler(pickle.Unpickler):\n",
    "    def find_class(self, module, name):\n",
    "        if module == \"torch.storage\" and name == \"_load_from_bytes\":\n",
    "            return lambda b: torch.load(io.BytesIO(b), map_location=\"cpu\")\n",
    "        else:\n",
    "            return super().find_class(module, name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "TaskName = \"CJ/new\"\n",
    "ins_dir = f\"/mnt/disk1/thlee/MILP/pas/instance/{TaskName}/train\"\n",
    "sol_dir = f\"/mnt/disk1/thlee/MILP/pas/dataset/{TaskName}/train/solution\"\n",
    "bg_dir = f\"/mnt/disk1/thlee/MILP/pas/dataset/{TaskName}/train/BG\"\n",
    "\n",
    "ins_names = sorted(os.listdir(ins_dir))\n",
    "# sols_path = sorted(glob(f\"{sol_dir}/*\"))\n",
    "# bgs_path = sorted(glob(f\"{bg_dir}/*\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Set parameter Username\n",
      "Academic license - for non-commercial use only - expires 2025-06-20\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S000.mps.gz\n",
      "Reading time = 1.19 seconds\n",
      "(null): 199866 rows, 124072 columns, 746370 nonzeros\n"
     ]
    }
   ],
   "source": [
    "for ins_name in ins_names:\n",
    "    sol_path = f\"{sol_dir}/{ins_name}.sol\"\n",
    "    # bg_path = f\"{bg_dir}/{ins_name}.bg\"\n",
    "\n",
    "    with open(sol_path, \"rb\") as f:\n",
    "        solData = pickle.load(f)\n",
    "    # with open(bg_path, \"rb\") as f:\n",
    "    #     bgData = CPU_Unpickler(f).load()\n",
    "    # A, v_map, v_nodes, c_nodes, b_vars = bgData\n",
    "    m = gp.read(f\"{ins_dir}/{ins_name}\")\n",
    "    mvars = m.getVars()\n",
    "    i_vars = [i.VarName for i in mvars if i.VType == \"I\"]\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_map = {var_name: i for i, var_name in enumerate(solData[\"var_names\"])}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "var_idx = v_map[i_vars[1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0., 100., 100.,\n",
       "       100., 100., 100., 100., 100., 100., 100., 100., 100., 100., 100.,\n",
       "       100., 100., 100., 100., 100., 100., 100., 100., 100., 100.,   0.,\n",
       "         0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "         0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "         0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var_idx += 1\n",
    "solData[\"sols\"][:, var_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(65, 124072)"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solData[\"sols\"].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [],
   "source": [
    "i_idxs = np.array([v_map[i] for i in i_vars])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = np.unique(solData[\"sols\"][:, i_idxs], return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiwAAAGsCAYAAAD+L/ysAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAeUUlEQVR4nO3df/DUdZ3A8dcCsiDy3QRC+MoXRKZS+4IRmOGPlDSMyDvvLqccJLS7P7gBhZguNbspu/JLc9U4N1fcyTk4jCmNo3BaZsAVmIGKIBdo508CUogg/K5gLsL3fX+Um18BY7/w3e9bfTxmdsb97Hu/n/fuW2afs5/P7hZSSikAADLWrasnAADwlwgWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHtdFiwPPPBAXHzxxdHY2BiFQiEWL15c899IKcW3vvWteO973xvFYjGamprixhtvPPqTBQC6VI+u2vGePXvi9NNPjyuvvDL+7u/+rkN/Y+bMmbFkyZL41re+FSNHjozW1tbYsWPHUZ4pANDVCjn8+GGhUIhFixbFJZdcUt22d+/e+PKXvxzf//7348UXX4zm5ub45je/Geeff35ERPzqV7+KUaNGxYYNG+J973tf10wcAKiLbM9hufLKK+MXv/hFLFy4MH75y1/GpZdeGh//+Mfj6aefjoiIe++9N04++eT44Q9/GMOHD4+TTjop/uEf/iF+//vfd/HMAYCjLctgefbZZ+OOO+6IO++8M84999wYMWJEfOELX4hzzjkn5s+fHxERzz33XGzatCnuvPPOWLBgQdx6662xZs2a+NSnPtXFswcAjrYuO4flzaxduzZSSvHe97633fZKpRL9+/ePiIi2traoVCqxYMGC6rhbbrklxowZE08++aTDRADwNpJlsLS1tUX37t1jzZo10b1793a3HXfccRERMXjw4OjRo0e7qDn11FMjImLz5s2CBQDeRrIMltGjR8f+/ftj+/btce655x50zNlnnx379u2LZ599NkaMGBEREU899VRERAwbNqxucwUAOl+XfUpo9+7d8cwzz0TEHwPlO9/5TowfPz769esXQ4cOjcsvvzx+8YtfxLe//e0YPXp07NixI37605/GyJEj4xOf+ES0tbXFGWecEccdd1zcdNNN0dbWFtOnT4+GhoZYsmRJVzwkAKCTdFmwLF++PMaPH3/A9qlTp8att94ar776anz961+PBQsWxPPPPx/9+/ePcePGxQ033BAjR46MiIgXXnghrrrqqliyZEn06dMnJk6cGN/+9rejX79+9X44AEAnyuJ7WAAA3kyWH2sGAHg9wQIAZK/unxJqa2uLF154Ifr27RuFQqHeuwcAOiClFC+99FI0NjZGt271f7+j7sHywgsvRFNTU713CwAcBVu2bIkhQ4bUfb91D5a+fftGxB8fcENDQ713DwB0QLlcjqampurreL3VPVheOwzU0NAgWADgLaarTudw0i0AkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2aspWE466aQoFAoHXKZPn95Z8wMAqO3HD1evXh379++vXt+wYUN87GMfi0svvfSoTwwA4DU1Bcu73/3udtfnzJkTI0aMiPPOO++oTgoA4PVqCpbX27t3b9x2220xe/bsN/2p6UqlEpVKpXq9XC53dJcAwDtUh0+6Xbx4cbz44otxxRVXvOm4lpaWKJVK1UtTU1NHdwkAvEMVUkqpI3e86KKLomfPnnHvvfe+6biDvcPS1NQUra2t0dDQ0JFdAwB1Vi6Xo1Qqddnrd4cOCW3atCmWLVsWd999918cWywWo1gsdmQ3AAAR0cFDQvPnz4+BAwfGpEmTjvZ8AAAOUHOwtLW1xfz582Pq1KnRo0eHz9kFADhsNQfLsmXLYvPmzfG5z32uM+YDAHCAmt8imTBhQnTwPF0AgA7xW0IAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZqzlYnn/++bj88sujf//+ceyxx8YHPvCBWLNmTWfMDQAgIiJ61DJ4165dcfbZZ8f48ePjxz/+cQwcODCeffbZeNe73tVJ0wMAqDFYvvnNb0ZTU1PMnz+/uu2kk0462nMCAGinpkNC99xzT4wdOzYuvfTSGDhwYIwePTrmzZv3pvepVCpRLpfbXQAAalFTsDz33HMxd+7ceM973hM/+clPYtq0aXH11VfHggULDnmflpaWKJVK1UtTU9MRTxoAeGcppJTS4Q7u2bNnjB07NlauXFnddvXVV8fq1atj1apVB71PpVKJSqVSvV4ul6OpqSlaW1ujoaHhCKYOANRLuVyOUqnUZa/fNb3DMnjw4DjttNPabTv11FNj8+bNh7xPsViMhoaGdhcAgFrUFCxnn312PPnkk+22PfXUUzFs2LCjOikAgNerKVg+//nPx0MPPRQ33nhjPPPMM3H77bfHzTffHNOnT++s+QEA1BYsZ5xxRixatCjuuOOOaG5ujn/5l3+Jm266KSZPntxZ8wMAqO2k26Ohq0/aAQBq19Wv335LCADInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDIXk3B8tWvfjUKhUK7y6BBgzprbgAAERHRo9Y7vP/9749ly5ZVr3fv3v2oTggA4I1qDpYePXp4VwUAqKuaz2F5+umno7GxMYYPHx6f+cxn4rnnnnvT8ZVKJcrlcrsLAEAtagqWM888MxYsWBA/+clPYt68ebFt27Y466yzYufOnYe8T0tLS5RKpeqlqanpiCcNALyzFFJKqaN33rNnT4wYMSK++MUvxuzZsw86plKpRKVSqV4vl8vR1NQUra2t0dDQ0NFdAwB1VC6Xo1Qqddnrd83nsLxenz59YuTIkfH0008fckyxWIxisXgkuwEA3uGO6HtYKpVK/OpXv4rBgwcfrfkAABygpmD5whe+ECtWrIiNGzfGww8/HJ/61KeiXC7H1KlTO2t+AAC1HRL6zW9+E5dddlns2LEj3v3ud8eHP/zheOihh2LYsGGdNT8AgNqCZeHChZ01DwCAQ/JbQgBA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9o4oWFpaWqJQKMSsWbOO0nQAAA7U4WBZvXp13HzzzTFq1KijOR8AgAN0KFh2794dkydPjnnz5sXxxx9/tOcEANBOh4Jl+vTpMWnSpLjwwgv/4thKpRLlcrndBQCgFj1qvcPChQtj7dq1sXr16sMa39LSEjfccEPNEwMAeE1N77Bs2bIlZs6cGbfddlv06tXrsO5z3XXXRWtra/WyZcuWDk0UAHjnKqSU0uEOXrx4cfzN3/xNdO/evbpt//79USgUolu3blGpVNrddjDlcjlKpVK0trZGQ0NDx2cOANRNV79+13RI6IILLoj169e323bllVfGKaecEtdcc81fjBUAgI6oKVj69u0bzc3N7bb16dMn+vfvf8B2AICjxTfdAgDZq/lTQm+0fPnyozANAIBD8w4LAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANkTLABA9gQLAJC9moJl7ty5MWrUqGhoaIiGhoYYN25c/PjHP+6suQEARESNwTJkyJCYM2dOPProo/Hoo4/GRz/60fjrv/7rePzxxztrfgAAUUgppSP5A/369Yt//dd/jb//+78/rPHlcjlKpVK0trZGQ0PDkewaAKiTrn797tHRO+7fvz/uvPPO2LNnT4wbN+6Q4yqVSlQqler1crnc0V0CAO9QNZ90u379+jjuuOOiWCzGtGnTYtGiRXHaaacdcnxLS0uUSqXqpamp6YgmDAC889R8SGjv3r2xefPmePHFF+Ouu+6K//qv/4oVK1YcMloO9g5LU1OTQ0IA8BbS1YeEjvgclgsvvDBGjBgR//mf/3lY47v6AQMAtevq1+8j/h6WlFK7d1AAAI62mk66/dKXvhQTJ06MpqameOmll2LhwoWxfPnyuP/++ztrfgAAtQXLb3/725gyZUps3bo1SqVSjBo1Ku6///742Mc+1lnzAwCoLVhuueWWzpoHAMAh+S0hACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7NQVLS0tLnHHGGdG3b98YOHBgXHLJJfHkk0921twAACKixmBZsWJFTJ8+PR566KFYunRp7Nu3LyZMmBB79uzprPkBAEQhpZQ6euff/e53MXDgwFixYkV85CMfOaz7lMvlKJVK0draGg0NDR3dNQBQR139+t3jSO7c2toaERH9+vU75JhKpRKVSqV6vVwuH8kuAYB3oA6fdJtSitmzZ8c555wTzc3NhxzX0tISpVKpemlqauroLgGAd6gOHxKaPn16/OhHP4oHH3wwhgwZcshxB3uHpampySEhAHgLeUseErrqqqvinnvuiQceeOBNYyUiolgsRrFY7NDkAAAiagyWlFJcddVVsWjRoli+fHkMHz68s+YFAFBVU7BMnz49br/99vjv//7v6Nu3b2zbti0iIkqlUvTu3btTJggAUNM5LIVC4aDb58+fH1dcccVh/Y2uPgYGANSuq1+/az4kBABQb35LCADInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDIXs3B8sADD8TFF18cjY2NUSgUYvHixZ0wLQCAP6s5WPbs2ROnn356/Pu//3tnzAcA4AA9ar3DxIkTY+LEiZ0xFwCAg6o5WGpVqVSiUqlUr5fL5c7eJQDwNtPpJ922tLREqVSqXpqamjp7lwDA20ynB8t1110Xra2t1cuWLVs6e5cAwNtMpx8SKhaLUSwWO3s3AMDbmO9hAQCyV/M7LLt3745nnnmmen3jxo2xbt266NevXwwdOvSoTg4AIKIDwfLoo4/G+PHjq9dnz54dERFTp06NW2+99ahNDADgNTUHy/nnnx8ppc6YCwDAQTmHBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHuCBQDInmABALInWACA7AkWACB7ggUAyJ5gAQCyJ1gAgOwJFgAge4IFAMieYAEAsidYAIDsCRYAIHsdCpbvfe97MXz48OjVq1eMGTMmfv7znx/teQEAVNUcLD/4wQ9i1qxZcf3118djjz0W5557bkycODE2b97cGfMDAIhCSinVcoczzzwzPvjBD8bcuXOr20499dS45JJLoqWl5S/ev1wuR6lUitbW1mhoaKh9xgBA3XX163ePWgbv3bs31qxZE9dee2277RMmTIiVK1ce9D6VSiUqlUr1erlcjoiI5q/8JLoVjz1g/JnD+8WJx/eO7oVCdCsUolu3QmwvvxK/3rknKvvaYsS7j4sTj+8dhYgoFCIKUYiIiLaUqtcLhfZ/87WrhTfe8Do79+yN37a+EqVjj4lBDb2ie7dDjwWAd5rKy7u7dP81BcuOHTti//79ccIJJ7TbfsIJJ8S2bdsOep+Wlpa44YYbDnsfD2/8fcTGQ9/+m11/OOy/BQAcHW2Vl7t0/zUFy2ve+E5FSumQ715cd911MXv27Or1crkcTU1NBx174akD47hij3jfoIZIkSKliLa2FE9t3x0rntwe5Vf2xamDG+Ki95/wp/3+af/x53dRqse3UvrjWzB/GpTajf/jfxTiz3PeuGNP/Gj91njXscfEZR8aGt3f5N2YN0qR2v2tjjjYnAAgF6/s2R3/fFPX7b+mYBkwYEB07979gHdTtm/ffsC7Lq8pFotRLBYP2L7hhouyO4flu109AQDIVLlcjn/uwv3X9Cmhnj17xpgxY2Lp0qXtti9dujTOOuusozoxAIDX1HxIaPbs2TFlypQYO3ZsjBs3Lm6++ebYvHlzTJs2rTPmBwBQe7B8+tOfjp07d8bXvva12Lp1azQ3N8d9990Xw4YN64z5AQDU/j0sR6qrP8cNANSuq1+//ZYQAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkL2av5r/SL32xbrlcrneuwYAOui11+06f0F+Vd2DZefOnRER0dTUVO9dAwBHaOfOnVEqleq+37oHS79+/SIiYvPmzV3ygPmzcrkcTU1NsWXLFr/r1MWsRT6sRT6sRV5aW1tj6NCh1dfxeqt7sHTr9sfTZkqlkv8BM9HQ0GAtMmEt8mEt8mEt8vLa63jd99slewUAqIFgAQCyV/dgKRaL8ZWvfCWKxWK9d80bWIt8WIt8WIt8WIu8dPV6FFJXfT4JAOAwOSQEAGRPsAAA2RMsAED2BAsAkL26Bsv3vve9GD58ePTq1SvGjBkTP//5z+u5+7edlpaWOOOMM6Jv374xcODAuOSSS+LJJ59sNyalFF/96lejsbExevfuHeeff348/vjj7cZUKpW46qqrYsCAAdGnT5/4q7/6q/jNb37TbsyuXbtiypQpUSqVolQqxZQpU+LFF1/s7If4ltXS0hKFQiFmzZpV3WYt6uf555+Pyy+/PPr37x/HHntsfOADH4g1a9ZUb7cW9bNv37748pe/HMOHD4/evXvHySefHF/72teira2tOsZ6dI4HHnggLr744mhsbIxCoRCLFy9ud3s9n/fNmzfHxRdfHH369IkBAwbE1VdfHXv37q3tAaU6WbhwYTrmmGPSvHnz0hNPPJFmzpyZ+vTpkzZt2lSvKbztXHTRRWn+/Plpw4YNad26dWnSpElp6NChaffu3dUxc+bMSX379k133XVXWr9+ffr0pz+dBg8enMrlcnXMtGnT0oknnpiWLl2a1q5dm8aPH59OP/30tG/fvuqYj3/846m5uTmtXLkyrVy5MjU3N6dPfvKTdX28bxWPPPJIOumkk9KoUaPSzJkzq9utRX38/ve/T8OGDUtXXHFFevjhh9PGjRvTsmXL0jPPPFMdYy3q5+tf/3rq379/+uEPf5g2btyY7rzzznTcccelm266qTrGenSO++67L11//fXprrvuShGRFi1a1O72ej3v+/btS83NzWn8+PFp7dq1aenSpamxsTHNmDGjpsdTt2D50Ic+lKZNm9Zu2ymnnJKuvfbaek3hbW/79u0pItKKFStSSim1tbWlQYMGpTlz5lTHvPLKK6lUKqX/+I//SCml9OKLL6ZjjjkmLVy4sDrm+eefT926dUv3339/SimlJ554IkVEeuihh6pjVq1alSIi/d///V89HtpbxksvvZTe8573pKVLl6bzzjuvGizWon6uueaadM455xzydmtRX5MmTUqf+9zn2m3727/923T55ZenlKxHvbwxWOr5vN93332pW7du6fnnn6+OueOOO1KxWEytra2H/Rjqckho7969sWbNmpgwYUK77RMmTIiVK1fWYwrvCK2trRHx5x+Y3LhxY2zbtq3d814sFuO8886rPu9r1qyJV199td2YxsbGaG5uro5ZtWpVlEqlOPPMM6tjPvzhD0epVLJ+bzB9+vSYNGlSXHjhhe22W4v6ueeee2Ls2LFx6aWXxsCBA2P06NExb9686u3Wor7OOeec+J//+Z946qmnIiLif//3f+PBBx+MT3ziExFhPbpKPZ/3VatWRXNzczQ2NlbHXHTRRVGpVNodqv1L6vLjhzt27Ij9+/fHCSec0G77CSecENu2bavHFN72Ukoxe/bsOOecc6K5uTkiovrcHux537RpU3VMz5494/jjjz9gzGv337ZtWwwcOPCAfQ4cOND6vc7ChQtj7dq1sXr16gNusxb189xzz8XcuXNj9uzZ8aUvfSkeeeSRuPrqq6NYLMZnP/tZa1Fn11xzTbS2tsYpp5wS3bt3j/3798c3vvGNuOyyyyLCv42uUs/nfdu2bQfs5/jjj4+ePXvWtDZ1/bXmQqHQ7npK6YBtdMyMGTPil7/8ZTz44IMH3NaR5/2NYw423vr92ZYtW2LmzJmxZMmS6NWr1yHHWYvO19bWFmPHjo0bb7wxIiJGjx4djz/+eMydOzc++9nPVsdZi/r4wQ9+ELfddlvcfvvt8f73vz/WrVsXs2bNisbGxpg6dWp1nPXoGvV63o/G2tTlkNCAAQOie/fuB5TU9u3bD6guanfVVVfFPffcEz/72c9iyJAh1e2DBg2KiHjT533QoEGxd+/e2LVr15uO+e1vf3vAfn/3u99Zvz9Zs2ZNbN++PcaMGRM9evSIHj16xIoVK+Lf/u3fokePHtXnyVp0vsGDB8dpp53Wbtupp54amzdvjgj/Lurtn/7pn+Laa6+Nz3zmMzFy5MiYMmVKfP7zn4+WlpaIsB5dpZ7P+6BBgw7Yz65du+LVV1+taW3qEiw9e/aMMWPGxNKlS9ttX7p0aZx11ln1mMLbUkopZsyYEXfffXf89Kc/jeHDh7e7ffjw4TFo0KB2z/vevXtjxYoV1ed9zJgxccwxx7Qbs3Xr1tiwYUN1zLhx46K1tTUeeeSR6piHH344Wltbrd+fXHDBBbF+/fpYt25d9TJ27NiYPHlyrFu3Lk4++WRrUSdnn332AR/vf+qpp2LYsGER4d9Fvb388svRrVv7l5ru3btXP9ZsPbpGPZ/3cePGxYYNG2Lr1q3VMUuWLIlisRhjxow5/Ekf9um5R+i1jzXfcsst6YknnkizZs1Kffr0Sb/+9a/rNYW3nX/8x39MpVIpLV++PG3durV6efnll6tj5syZk0qlUrr77rvT+vXr02WXXXbQj60NGTIkLVu2LK1duzZ99KMfPejH1kaNGpVWrVqVVq1alUaOHPmO/rjg4Xj9p4RSshb18sgjj6QePXqkb3zjG+npp59O3//+99Oxxx6bbrvttuoYa1E/U6dOTSeeeGL1Y8133313GjBgQPriF79YHWM9OsdLL72UHnvssfTYY4+liEjf+c530mOPPVb9OpF6Pe+vfaz5ggsuSGvXrk3Lli1LQ4YMyfdjzSml9N3vfjcNGzYs9ezZM33wgx+sfvyWjomIg17mz59fHdPW1pa+8pWvpEGDBqVisZg+8pGPpPXr17f7O3/4wx/SjBkzUr9+/VLv3r3TJz/5ybR58+Z2Y3bu3JkmT56c+vbtm/r27ZsmT56cdu3aVYdH+db1xmCxFvVz7733pubm5lQsFtMpp5ySbr755na3W4v6KZfLaebMmWno0KGpV69e6eSTT07XX399qlQq1THWo3P87Gc/O+hrxNSpU1NK9X3eN23alCZNmpR69+6d+vXrl2bMmJFeeeWVmh5PIaWUDv/9GACA+vNbQgBA9gQLAJA9wQIAZE+wAADZEywAQPYECwCQPcECAGRPsAAA2RMsAED2BAsAkD3BAgBkT7AAANn7f/528qxUWXcnAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \"-\", label=\"Gurobi\")\n",
    "# plt.xscale(\"log\")\n",
    "# plt.yscale(\"log\")\n",
    "# plt.xlabel(\"time (sec)\")\n",
    "# plt.ylabel(\"Incumbent solution’s objective value\")\n",
    "# plt.title(f\"{par}_{d_type}\")\n",
    "# plt.legend()\n",
    "plt.xlim([0, 10000])\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistics of coefficient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import io\n",
    "import os\n",
    "import pickle\n",
    "from glob import glob\n",
    "\n",
    "import gurobipy as gp\n",
    "import numpy as np\n",
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "TaskName = \"CJ/new\"\n",
    "ins_dir = f\"/mnt/disk1/thlee/MILP/pas/instance/{TaskName}/train\"\n",
    "sol_dir = f\"/mnt/disk1/thlee/MILP/pas/dataset/{TaskName}/train/solution\"\n",
    "bg_dir = f\"/mnt/disk1/thlee/MILP/pas/dataset/{TaskName}/train/BG\"\n",
    "\n",
    "ins_names = sorted(os.listdir(ins_dir))\n",
    "# sols_path = sorted(glob(f\"{sol_dir}/*\"))\n",
    "# bgs_path = sorted(glob(f\"{bg_dir}/*\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S000.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199866 rows, 124072 columns, 746370 nonzeros\n",
      "S000.mps.gz rate: 0.9333290347540139\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S001.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199818 rows, 127207 columns, 761519 nonzeros\n",
      "S001.mps.gz rate: 0.9142578631679074\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S002.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199865 rows, 139089 columns, 842959 nonzeros\n",
      "S002.mps.gz rate: 0.842625944539108\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S003.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199816 rows, 120949 columns, 726847 nonzeros\n",
      "S003.mps.gz rate: 0.9698302590347998\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S004.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199763 rows, 130275 columns, 781821 nonzeros\n",
      "S004.mps.gz rate: 0.9080790635194781\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S005.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200006 rows, 130180 columns, 799664 nonzeros\n",
      "S005.mps.gz rate: 0.9049009064372406\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S006.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199910 rows, 138915 columns, 834093 nonzeros\n",
      "S006.mps.gz rate: 0.8472807112262895\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S007.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199956 rows, 125015 columns, 764225 nonzeros\n",
      "S007.mps.gz rate: 0.9238891333040036\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S008.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199690 rows, 123943 columns, 737252 nonzeros\n",
      "S008.mps.gz rate: 0.9391413795050951\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S009.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199928 rows, 129775 columns, 789910 nonzeros\n",
      "S009.mps.gz rate: 0.8977075707956078\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S010.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199796 rows, 118386 columns, 715087 nonzeros\n",
      "S010.mps.gz rate: 0.9756221174801074\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S011.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199897 rows, 128891 columns, 778410 nonzeros\n",
      "S011.mps.gz rate: 0.896106012056699\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S012.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199923 rows, 137779 columns, 832659 nonzeros\n",
      "S012.mps.gz rate: 0.8441054151938975\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S013.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199908 rows, 148003 columns, 898909 nonzeros\n",
      "S013.mps.gz rate: 0.7945784882738863\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S014.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199842 rows, 132376 columns, 792962 nonzeros\n",
      "S014.mps.gz rate: 0.8906448298785279\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S015.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199913 rows, 156244 columns, 954746 nonzeros\n",
      "S015.mps.gz rate: 0.759069148255293\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S016.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199876 rows, 124172 columns, 747597 nonzeros\n",
      "S016.mps.gz rate: 0.9293560545050414\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S017.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199881 rows, 132031 columns, 790925 nonzeros\n",
      "S017.mps.gz rate: 0.8725223621725201\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S018.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199886 rows, 132180 columns, 800762 nonzeros\n",
      "S018.mps.gz rate: 0.8707822666061432\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S019.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199759 rows, 124086 columns, 744335 nonzeros\n",
      "S019.mps.gz rate: 0.9388649807391647\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S020.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199912 rows, 122343 columns, 744013 nonzeros\n",
      "S020.mps.gz rate: 0.9416149677545915\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S021.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199738 rows, 133561 columns, 804671 nonzeros\n",
      "S021.mps.gz rate: 0.8849888814848645\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S022.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199662 rows, 122930 columns, 733460 nonzeros\n",
      "S022.mps.gz rate: 0.9550150492150004\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S023.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199779 rows, 127382 columns, 760639 nonzeros\n",
      "S023.mps.gz rate: 0.90672151481371\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S024.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199879 rows, 126219 columns, 754639 nonzeros\n",
      "S024.mps.gz rate: 0.9340907470349155\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S025.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199944 rows, 122424 columns, 739195 nonzeros\n",
      "S025.mps.gz rate: 0.9352741292557014\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S026.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199925 rows, 133857 columns, 807235 nonzeros\n",
      "S026.mps.gz rate: 0.8658493765735076\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S027.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199965 rows, 139768 columns, 853833 nonzeros\n",
      "S027.mps.gz rate: 0.8356705397515883\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S028.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199590 rows, 126071 columns, 751433 nonzeros\n",
      "S028.mps.gz rate: 0.9367737227435333\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S029.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199996 rows, 127811 columns, 785209 nonzeros\n",
      "S029.mps.gz rate: 0.9107197346081323\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S030.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199874 rows, 120363 columns, 721044 nonzeros\n",
      "S030.mps.gz rate: 0.9670745993370056\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S031.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199555 rows, 123406 columns, 731238 nonzeros\n",
      "S031.mps.gz rate: 0.9497107109864998\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S032.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199969 rows, 135628 columns, 821351 nonzeros\n",
      "S032.mps.gz rate: 0.8611791075589112\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S033.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199881 rows, 129179 columns, 781774 nonzeros\n",
      "S033.mps.gz rate: 0.9003011325370223\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S034.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199782 rows, 115438 columns, 692745 nonzeros\n",
      "S034.mps.gz rate: 0.9918744260988583\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S035.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199852 rows, 121821 columns, 735010 nonzeros\n",
      "S035.mps.gz rate: 0.9596046658622077\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S036.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199804 rows, 135602 columns, 814610 nonzeros\n",
      "S036.mps.gz rate: 0.8591318712113392\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S037.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199997 rows, 140245 columns, 854529 nonzeros\n",
      "S037.mps.gz rate: 0.8299761132304182\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S038.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199840 rows, 125038 columns, 754293 nonzeros\n",
      "S038.mps.gz rate: 0.9301172443577153\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S039.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200022 rows, 143780 columns, 878457 nonzeros\n",
      "S039.mps.gz rate: 0.8193072750034774\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S040.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199988 rows, 129235 columns, 783465 nonzeros\n",
      "S040.mps.gz rate: 0.8991372306263783\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S041.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200066 rows, 134307 columns, 817424 nonzeros\n",
      "S041.mps.gz rate: 0.8555026915946302\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S042.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200109 rows, 135966 columns, 836616 nonzeros\n",
      "S042.mps.gz rate: 0.857567333009723\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S043.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199806 rows, 126985 columns, 773194 nonzeros\n",
      "S043.mps.gz rate: 0.9379060518958933\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S044.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199939 rows, 138728 columns, 842432 nonzeros\n",
      "S044.mps.gz rate: 0.8412144628337466\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S045.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199996 rows, 140774 columns, 858478 nonzeros\n",
      "S045.mps.gz rate: 0.8346711750749427\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S046.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199903 rows, 128575 columns, 776129 nonzeros\n",
      "S046.mps.gz rate: 0.8990861364962084\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S047.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199884 rows, 131631 columns, 800719 nonzeros\n",
      "S047.mps.gz rate: 0.8903677705099863\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S048.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199912 rows, 131687 columns, 805911 nonzeros\n",
      "S048.mps.gz rate: 0.8899891409174786\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S049.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199873 rows, 139734 columns, 846630 nonzeros\n",
      "S049.mps.gz rate: 0.8380208109694133\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S050.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199874 rows, 133621 columns, 811641 nonzeros\n",
      "S050.mps.gz rate: 0.8756108695489482\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S051.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199954 rows, 139917 columns, 848264 nonzeros\n",
      "S051.mps.gz rate: 0.8447865520272734\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S052.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199975 rows, 125445 columns, 766934 nonzeros\n",
      "S052.mps.gz rate: 0.9326796604089441\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S053.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199958 rows, 125195 columns, 760160 nonzeros\n",
      "S053.mps.gz rate: 0.9289508366947561\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S054.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199883 rows, 121812 columns, 736491 nonzeros\n",
      "S054.mps.gz rate: 0.9531080681706235\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S055.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199944 rows, 130008 columns, 783660 nonzeros\n",
      "S055.mps.gz rate: 0.889176050704572\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S056.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199916 rows, 124847 columns, 745817 nonzeros\n",
      "S056.mps.gz rate: 0.9219284404110631\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S057.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199946 rows, 135667 columns, 822729 nonzeros\n",
      "S057.mps.gz rate: 0.866828337031113\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S058.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199850 rows, 118056 columns, 708115 nonzeros\n",
      "S058.mps.gz rate: 0.9808904248831064\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S059.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199891 rows, 129111 columns, 784426 nonzeros\n",
      "S059.mps.gz rate: 0.8969026651485931\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S060.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199891 rows, 128942 columns, 788579 nonzeros\n",
      "S060.mps.gz rate: 0.9042825456406757\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S061.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199663 rows, 137965 columns, 821234 nonzeros\n",
      "S061.mps.gz rate: 0.8567390280143515\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S062.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200019 rows, 126116 columns, 763364 nonzeros\n",
      "S062.mps.gz rate: 0.9126518443337879\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S063.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199690 rows, 124790 columns, 747343 nonzeros\n",
      "S063.mps.gz rate: 0.9247535860245212\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S064.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199891 rows, 138776 columns, 840272 nonzeros\n",
      "S064.mps.gz rate: 0.8474087738513865\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S065.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199750 rows, 132403 columns, 800603 nonzeros\n",
      "S065.mps.gz rate: 0.8942395565055171\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S066.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199848 rows, 141312 columns, 853123 nonzeros\n",
      "S066.mps.gz rate: 0.8350317028985508\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S067.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199859 rows, 130302 columns, 797991 nonzeros\n",
      "S067.mps.gz rate: 0.9002164203158816\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S068.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199758 rows, 124733 columns, 752481 nonzeros\n",
      "S068.mps.gz rate: 0.9347967258063222\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S069.mps.gz\n",
      "Reading time = 0.27 seconds\n",
      "(null): 199767 rows, 105225 columns, 624548 nonzeros\n",
      "S069.mps.gz rate: 1.1014492753623188\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S070.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199978 rows, 133972 columns, 823932 nonzeros\n",
      "S070.mps.gz rate: 0.8807810587286895\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S071.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199985 rows, 146691 columns, 897571 nonzeros\n",
      "S071.mps.gz rate: 0.8057754054440968\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S072.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199896 rows, 140251 columns, 852498 nonzeros\n",
      "S072.mps.gz rate: 0.8427747395740494\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S073.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200051 rows, 128426 columns, 779591 nonzeros\n",
      "S073.mps.gz rate: 0.8993505987884074\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S074.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199959 rows, 148987 columns, 909985 nonzeros\n",
      "S074.mps.gz rate: 0.7933578097417895\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S075.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199876 rows, 138009 columns, 841537 nonzeros\n",
      "S075.mps.gz rate: 0.8521183401082538\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S076.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199925 rows, 136146 columns, 833359 nonzeros\n",
      "S076.mps.gz rate: 0.8608405682135355\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S077.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199777 rows, 134135 columns, 802781 nonzeros\n",
      "S077.mps.gz rate: 0.8640548700935625\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S078.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199795 rows, 135792 columns, 821898 nonzeros\n",
      "S078.mps.gz rate: 0.8630847178036997\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S079.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199888 rows, 131201 columns, 800129 nonzeros\n",
      "S079.mps.gz rate: 0.8978590102209586\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S080.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200039 rows, 135855 columns, 828178 nonzeros\n",
      "S080.mps.gz rate: 0.8567958485149608\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S081.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199893 rows, 134718 columns, 818611 nonzeros\n",
      "S081.mps.gz rate: 0.8669962440059977\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S082.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199851 rows, 111392 columns, 671921 nonzeros\n",
      "S082.mps.gz rate: 1.0296969261706406\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S083.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199870 rows, 150185 columns, 909273 nonzeros\n",
      "S083.mps.gz rate: 0.7896927123214702\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S084.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199933 rows, 143280 columns, 870921 nonzeros\n",
      "S084.mps.gz rate: 0.8186767169179229\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S085.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199633 rows, 138172 columns, 816694 nonzeros\n",
      "S085.mps.gz rate: 0.8424282777986857\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S086.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199810 rows, 123562 columns, 747243 nonzeros\n",
      "S086.mps.gz rate: 0.9347534031498357\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S087.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199900 rows, 136200 columns, 831174 nonzeros\n",
      "S087.mps.gz rate: 0.869309838472834\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S088.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199604 rows, 135522 columns, 802879 nonzeros\n",
      "S088.mps.gz rate: 0.8625905756998864\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S089.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199774 rows, 117870 columns, 699581 nonzeros\n",
      "S089.mps.gz rate: 0.9824382794604226\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S090.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199981 rows, 132333 columns, 804750 nonzeros\n",
      "S090.mps.gz rate: 0.8879115564522833\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S091.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199812 rows, 132264 columns, 792368 nonzeros\n",
      "S091.mps.gz rate: 0.8861065747293293\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S092.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200018 rows, 135986 columns, 835351 nonzeros\n",
      "S092.mps.gz rate: 0.8589119468180547\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S093.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199942 rows, 133430 columns, 812286 nonzeros\n",
      "S093.mps.gz rate: 0.8708686202503184\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S094.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199857 rows, 127567 columns, 770783 nonzeros\n",
      "S094.mps.gz rate: 0.9179489993493615\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S095.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199886 rows, 142148 columns, 852899 nonzeros\n",
      "S095.mps.gz rate: 0.8216788136308636\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S096.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199857 rows, 126075 columns, 767761 nonzeros\n",
      "S096.mps.gz rate: 0.9343644655958754\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S097.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199872 rows, 133183 columns, 803572 nonzeros\n",
      "S097.mps.gz rate: 0.8754871117184626\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S098.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199621 rows, 121199 columns, 723085 nonzeros\n",
      "S098.mps.gz rate: 0.9595788744131553\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S099.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199715 rows, 121134 columns, 728185 nonzeros\n",
      "S099.mps.gz rate: 0.9658725048293626\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S100.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199770 rows, 116452 columns, 699599 nonzeros\n",
      "S100.mps.gz rate: 0.986672620478824\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S101.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199973 rows, 150691 columns, 908958 nonzeros\n",
      "S101.mps.gz rate: 0.7830593731543357\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S102.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199610 rows, 119770 columns, 707622 nonzeros\n",
      "S102.mps.gz rate: 0.9685230024213075\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S103.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199849 rows, 120569 columns, 732498 nonzeros\n",
      "S103.mps.gz rate: 0.9753750964178189\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S104.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199876 rows, 120643 columns, 719805 nonzeros\n",
      "S104.mps.gz rate: 0.9615145511965054\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S105.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200031 rows, 131690 columns, 790715 nonzeros\n",
      "S105.mps.gz rate: 0.8755410433594046\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S106.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199578 rows, 122774 columns, 728961 nonzeros\n",
      "S106.mps.gz rate: 0.9651880691351589\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S107.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199895 rows, 149968 columns, 907599 nonzeros\n",
      "S107.mps.gz rate: 0.7928358049717273\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S108.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199968 rows, 139993 columns, 849502 nonzeros\n",
      "S108.mps.gz rate: 0.8343274306572471\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S109.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199922 rows, 125481 columns, 756145 nonzeros\n",
      "S109.mps.gz rate: 0.9260366111204087\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S110.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199881 rows, 127946 columns, 769694 nonzeros\n",
      "S110.mps.gz rate: 0.9050693261219578\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S111.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199718 rows, 113603 columns, 671603 nonzeros\n",
      "S111.mps.gz rate: 1.0210997948997826\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S112.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199867 rows, 132523 columns, 810124 nonzeros\n",
      "S112.mps.gz rate: 0.8851293737690816\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S113.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199938 rows, 139099 columns, 842658 nonzeros\n",
      "S113.mps.gz rate: 0.8475977541175709\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S114.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199994 rows, 146145 columns, 893122 nonzeros\n",
      "S114.mps.gz rate: 0.8101542988128229\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S115.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199960 rows, 145412 columns, 883888 nonzeros\n",
      "S115.mps.gz rate: 0.8087365554424668\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S116.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199910 rows, 137852 columns, 825839 nonzeros\n",
      "S116.mps.gz rate: 0.8516379885674491\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S117.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199820 rows, 128576 columns, 776650 nonzeros\n",
      "S117.mps.gz rate: 0.9263003982080638\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S118.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199934 rows, 137392 columns, 834323 nonzeros\n",
      "S118.mps.gz rate: 0.8479387446139514\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S119.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199891 rows, 139035 columns, 841200 nonzeros\n",
      "S119.mps.gz rate: 0.8479879167116193\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S120.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199790 rows, 126681 columns, 758737 nonzeros\n",
      "S120.mps.gz rate: 0.9109495504456074\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S121.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199812 rows, 131678 columns, 788865 nonzeros\n",
      "S121.mps.gz rate: 0.8847339722656784\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S122.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199713 rows, 116799 columns, 700796 nonzeros\n",
      "S122.mps.gz rate: 1.0128511374241218\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S123.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199783 rows, 117851 columns, 712754 nonzeros\n",
      "S123.mps.gz rate: 0.9851422558993983\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S124.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199915 rows, 138443 columns, 842366 nonzeros\n",
      "S124.mps.gz rate: 0.842946194462703\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S125.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199812 rows, 134977 columns, 810054 nonzeros\n",
      "S125.mps.gz rate: 0.8682960800729013\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S126.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199742 rows, 130978 columns, 779109 nonzeros\n",
      "S126.mps.gz rate: 0.891752813449587\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S127.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199811 rows, 142162 columns, 850926 nonzeros\n",
      "S127.mps.gz rate: 0.8237081639256622\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S128.mps.gz\n",
      "Reading time = 0.37 seconds\n",
      "(null): 199945 rows, 151903 columns, 917240 nonzeros\n",
      "S128.mps.gz rate: 0.7774698327221977\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S129.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199813 rows, 117691 columns, 713560 nonzeros\n",
      "S129.mps.gz rate: 0.9839325012107978\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S130.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199818 rows, 126279 columns, 758453 nonzeros\n",
      "S130.mps.gz rate: 0.927311746212751\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S131.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199928 rows, 132286 columns, 808846 nonzeros\n",
      "S131.mps.gz rate: 0.8889829611599112\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S132.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199768 rows, 122352 columns, 739070 nonzeros\n",
      "S132.mps.gz rate: 0.9554400418464757\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S133.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199730 rows, 138511 columns, 836892 nonzeros\n",
      "S133.mps.gz rate: 0.8446982550122374\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S134.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199865 rows, 129528 columns, 780920 nonzeros\n",
      "S134.mps.gz rate: 0.8886109567043419\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S135.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199721 rows, 120380 columns, 714272 nonzeros\n",
      "S135.mps.gz rate: 0.9661073267984716\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S136.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200005 rows, 126132 columns, 772044 nonzeros\n",
      "S136.mps.gz rate: 0.9125360733200141\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S137.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199710 rows, 109352 columns, 652193 nonzeros\n",
      "S137.mps.gz rate: 1.0571365864364621\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S138.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199981 rows, 130991 columns, 793175 nonzeros\n",
      "S138.mps.gz rate: 0.8878472566817567\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S139.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199962 rows, 135084 columns, 821133 nonzeros\n",
      "S139.mps.gz rate: 0.8609457818838648\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S140.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199992 rows, 136881 columns, 827082 nonzeros\n",
      "S140.mps.gz rate: 0.848912559084168\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S141.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199899 rows, 128578 columns, 782324 nonzeros\n",
      "S141.mps.gz rate: 0.9037315870522175\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S142.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199827 rows, 135643 columns, 810803 nonzeros\n",
      "S142.mps.gz rate: 0.8529743517910988\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S143.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199702 rows, 130750 columns, 782973 nonzeros\n",
      "S143.mps.gz rate: 0.8879541108986616\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S144.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200024 rows, 112584 columns, 691530 nonzeros\n",
      "S144.mps.gz rate: 1.0303417892418105\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S145.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199638 rows, 115313 columns, 691095 nonzeros\n",
      "S145.mps.gz rate: 1.008559312479946\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S146.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199965 rows, 142817 columns, 865879 nonzeros\n",
      "S146.mps.gz rate: 0.8220309907083891\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S147.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199891 rows, 131244 columns, 802755 nonzeros\n",
      "S147.mps.gz rate: 0.899088720246259\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S148.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199761 rows, 128716 columns, 782924 nonzeros\n",
      "S148.mps.gz rate: 0.9151931383821748\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S149.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199862 rows, 136299 columns, 812022 nonzeros\n",
      "S149.mps.gz rate: 0.8591405659615992\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S150.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200023 rows, 146907 columns, 890323 nonzeros\n",
      "S150.mps.gz rate: 0.790295901488697\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S151.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200109 rows, 141504 columns, 866541 nonzeros\n",
      "S151.mps.gz rate: 0.8289518317503393\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S152.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 200000 rows, 129979 columns, 805306 nonzeros\n",
      "S152.mps.gz rate: 0.8970679879057386\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S153.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199859 rows, 131354 columns, 796251 nonzeros\n",
      "S153.mps.gz rate: 0.8861549705376311\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S154.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199805 rows, 119712 columns, 719152 nonzeros\n",
      "S154.mps.gz rate: 0.9748396150761828\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S155.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199878 rows, 125827 columns, 770561 nonzeros\n",
      "S155.mps.gz rate: 0.9322323507673234\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S156.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199932 rows, 131180 columns, 798087 nonzeros\n",
      "S156.mps.gz rate: 0.8858057630736392\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S157.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199799 rows, 126438 columns, 764127 nonzeros\n",
      "S157.mps.gz rate: 0.9190275075531089\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S158.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199907 rows, 146982 columns, 889135 nonzeros\n",
      "S158.mps.gz rate: 0.8041801036861658\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S159.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199963 rows, 132484 columns, 804014 nonzeros\n",
      "S159.mps.gz rate: 0.8793514688566166\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S160.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199642 rows, 120911 columns, 724570 nonzeros\n",
      "S160.mps.gz rate: 0.9792326587324561\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S161.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199906 rows, 141144 columns, 856262 nonzeros\n",
      "S161.mps.gz rate: 0.8346086266507964\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S162.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199974 rows, 135886 columns, 827094 nonzeros\n",
      "S162.mps.gz rate: 0.8610158515225999\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S163.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199771 rows, 131622 columns, 790602 nonzeros\n",
      "S163.mps.gz rate: 0.9033444257039096\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S164.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199953 rows, 143401 columns, 871082 nonzeros\n",
      "S164.mps.gz rate: 0.8193806179873222\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S165.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199891 rows, 133550 columns, 811865 nonzeros\n",
      "S165.mps.gz rate: 0.8685885436166231\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S166.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199540 rows, 120001 columns, 708574 nonzeros\n",
      "S166.mps.gz rate: 0.9791585070124416\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S167.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199634 rows, 116924 columns, 691816 nonzeros\n",
      "S167.mps.gz rate: 0.9886764051862748\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S168.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199976 rows, 131554 columns, 798669 nonzeros\n",
      "S168.mps.gz rate: 0.8832874713045594\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S169.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199843 rows, 124900 columns, 757502 nonzeros\n",
      "S169.mps.gz rate: 0.9231385108086468\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S170.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199662 rows, 136354 columns, 812938 nonzeros\n",
      "S170.mps.gz rate: 0.8661278730363613\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S171.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199955 rows, 130376 columns, 792177 nonzeros\n",
      "S171.mps.gz rate: 0.8866662575934221\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S172.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199990 rows, 137947 columns, 845452 nonzeros\n",
      "S172.mps.gz rate: 0.8539511551537908\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S173.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 200004 rows, 153143 columns, 929325 nonzeros\n",
      "S173.mps.gz rate: 0.7705216692894876\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S174.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199911 rows, 134714 columns, 819325 nonzeros\n",
      "S174.mps.gz rate: 0.8662796739759787\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S175.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199774 rows, 120595 columns, 719780 nonzeros\n",
      "S175.mps.gz rate: 0.9701894771756706\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S176.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199808 rows, 132906 columns, 801209 nonzeros\n",
      "S176.mps.gz rate: 0.8908551908867921\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S177.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199692 rows, 134470 columns, 801107 nonzeros\n",
      "S177.mps.gz rate: 0.8693388859968766\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S178.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199815 rows, 124520 columns, 741018 nonzeros\n",
      "S178.mps.gz rate: 0.9388050112431737\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S179.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199773 rows, 110823 columns, 665260 nonzeros\n",
      "S179.mps.gz rate: 1.0548351876415545\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S180.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199995 rows, 144473 columns, 876451 nonzeros\n",
      "S180.mps.gz rate: 0.8146850968693112\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S181.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199826 rows, 125858 columns, 758069 nonzeros\n",
      "S181.mps.gz rate: 0.9296190945351109\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S182.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199829 rows, 133810 columns, 814568 nonzeros\n",
      "S182.mps.gz rate: 0.8811000672595471\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S183.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199965 rows, 118455 columns, 719054 nonzeros\n",
      "S183.mps.gz rate: 0.9860284496222194\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S184.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199792 rows, 137687 columns, 832514 nonzeros\n",
      "S184.mps.gz rate: 0.8519322811884926\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S185.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199955 rows, 138628 columns, 847543 nonzeros\n",
      "S185.mps.gz rate: 0.8533629569783883\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S186.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199743 rows, 132310 columns, 782213 nonzeros\n",
      "S186.mps.gz rate: 0.8812636988889729\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S187.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199702 rows, 119612 columns, 715415 nonzeros\n",
      "S187.mps.gz rate: 0.9764906531117279\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S188.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199861 rows, 130460 columns, 785847 nonzeros\n",
      "S188.mps.gz rate: 0.8975931319944811\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S189.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199873 rows, 126921 columns, 767188 nonzeros\n",
      "S189.mps.gz rate: 0.91710591627863\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S190.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199969 rows, 131151 columns, 793338 nonzeros\n",
      "S190.mps.gz rate: 0.8821892322589993\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S191.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199954 rows, 125706 columns, 767675 nonzeros\n",
      "S191.mps.gz rate: 0.9204015719217858\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S192.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199836 rows, 139410 columns, 836768 nonzeros\n",
      "S192.mps.gz rate: 0.8428376730507137\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S193.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200040 rows, 141508 columns, 875560 nonzeros\n",
      "S193.mps.gz rate: 0.8296350736354128\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S194.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199962 rows, 143733 columns, 874745 nonzeros\n",
      "S194.mps.gz rate: 0.8209666534477121\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S195.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199728 rows, 118857 columns, 705700 nonzeros\n",
      "S195.mps.gz rate: 0.977645405823805\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S196.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199858 rows, 128626 columns, 774092 nonzeros\n",
      "S196.mps.gz rate: 0.9033943370702657\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S197.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199675 rows, 116642 columns, 696703 nonzeros\n",
      "S197.mps.gz rate: 0.9979252756297045\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S198.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199957 rows, 125109 columns, 762717 nonzeros\n",
      "S198.mps.gz rate: 0.9367831251148997\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S199.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199803 rows, 126513 columns, 762785 nonzeros\n",
      "S199.mps.gz rate: 0.9200635507813427\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S200.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199918 rows, 115398 columns, 706808 nonzeros\n",
      "S200.mps.gz rate: 1.010416125062826\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S201.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199695 rows, 125637 columns, 753540 nonzeros\n",
      "S201.mps.gz rate: 0.9296624402047168\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S202.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199888 rows, 118530 columns, 713981 nonzeros\n",
      "S202.mps.gz rate: 0.9854045389352907\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S203.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199721 rows, 118198 columns, 707251 nonzeros\n",
      "S203.mps.gz rate: 0.9771738946513477\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S204.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199869 rows, 132156 columns, 804517 nonzeros\n",
      "S204.mps.gz rate: 0.8868307152153516\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S205.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199814 rows, 140466 columns, 850703 nonzeros\n",
      "S205.mps.gz rate: 0.8471801005225463\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S206.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199838 rows, 142405 columns, 859653 nonzeros\n",
      "S206.mps.gz rate: 0.8201959200870755\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S207.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199716 rows, 134134 columns, 795044 nonzeros\n",
      "S207.mps.gz rate: 0.8625702655553402\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S208.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199900 rows, 134107 columns, 811661 nonzeros\n",
      "S208.mps.gz rate: 0.8634896015867927\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S209.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199980 rows, 134567 columns, 815477 nonzeros\n",
      "S209.mps.gz rate: 0.8716847369711742\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S210.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199862 rows, 124948 columns, 756294 nonzeros\n",
      "S210.mps.gz rate: 0.9435925344943497\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S211.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199668 rows, 122607 columns, 733081 nonzeros\n",
      "S211.mps.gz rate: 0.9452967611963428\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S212.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199857 rows, 126107 columns, 763564 nonzeros\n",
      "S212.mps.gz rate: 0.9285765262832356\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S213.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199756 rows, 129635 columns, 780679 nonzeros\n",
      "S213.mps.gz rate: 0.9117907972384001\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S214.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199628 rows, 109807 columns, 650182 nonzeros\n",
      "S214.mps.gz rate: 1.0573096432832152\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S215.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199990 rows, 144702 columns, 878930 nonzeros\n",
      "S215.mps.gz rate: 0.8113225801993063\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S216.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199667 rows, 118706 columns, 711977 nonzeros\n",
      "S216.mps.gz rate: 0.9856283591393863\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S217.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199779 rows, 125950 columns, 751584 nonzeros\n",
      "S217.mps.gz rate: 0.9194124652639937\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S218.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199913 rows, 126793 columns, 770555 nonzeros\n",
      "S218.mps.gz rate: 0.9235525620499554\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S219.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199957 rows, 137949 columns, 837925 nonzeros\n",
      "S219.mps.gz rate: 0.8546636800556726\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S220.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199589 rows, 120863 columns, 713310 nonzeros\n",
      "S220.mps.gz rate: 0.9705203412127781\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S221.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199802 rows, 113036 columns, 674646 nonzeros\n",
      "S221.mps.gz rate: 1.011182278212251\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S222.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199896 rows, 119650 columns, 720490 nonzeros\n",
      "S222.mps.gz rate: 0.9611366485582951\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S223.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199883 rows, 120640 columns, 732258 nonzeros\n",
      "S223.mps.gz rate: 0.9673408488063661\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S224.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199843 rows, 130747 columns, 787198 nonzeros\n",
      "S224.mps.gz rate: 0.8925635005009674\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S225.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199785 rows, 128418 columns, 767628 nonzeros\n",
      "S225.mps.gz rate: 0.9103085237272034\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S226.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199888 rows, 112134 columns, 670703 nonzeros\n",
      "S226.mps.gz rate: 1.0273422869067366\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S227.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199764 rows, 129629 columns, 782625 nonzeros\n",
      "S227.mps.gz rate: 0.9102901356949448\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S228.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199829 rows, 127859 columns, 768173 nonzeros\n",
      "S228.mps.gz rate: 0.911942061176765\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S229.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199800 rows, 133997 columns, 807442 nonzeros\n",
      "S229.mps.gz rate: 0.8806167302253035\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S230.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199762 rows, 122302 columns, 733342 nonzeros\n",
      "S230.mps.gz rate: 0.9501071119033213\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S231.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199766 rows, 131759 columns, 793690 nonzeros\n",
      "S231.mps.gz rate: 0.8834311128651554\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S232.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199863 rows, 129866 columns, 791038 nonzeros\n",
      "S232.mps.gz rate: 0.896308502610383\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S233.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199758 rows, 114725 columns, 694083 nonzeros\n",
      "S233.mps.gz rate: 1.0050119851819568\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S234.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199868 rows, 129234 columns, 777293 nonzeros\n",
      "S234.mps.gz rate: 0.9053345094944055\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S235.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199951 rows, 134553 columns, 816912 nonzeros\n",
      "S235.mps.gz rate: 0.8613706123237683\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S236.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199771 rows, 121538 columns, 733727 nonzeros\n",
      "S236.mps.gz rate: 0.9659530352646909\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S237.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199589 rows, 136828 columns, 810823 nonzeros\n",
      "S237.mps.gz rate: 0.8514339170345251\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S238.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199867 rows, 125243 columns, 758851 nonzeros\n",
      "S238.mps.gz rate: 0.945362215852383\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S239.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199651 rows, 140374 columns, 840968 nonzeros\n",
      "S239.mps.gz rate: 0.843461039793694\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S240.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199957 rows, 132915 columns, 806045 nonzeros\n",
      "S240.mps.gz rate: 0.8749952977466802\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S241.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199813 rows, 137439 columns, 826938 nonzeros\n",
      "S241.mps.gz rate: 0.8541971347288615\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S242.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199880 rows, 122926 columns, 743400 nonzeros\n",
      "S242.mps.gz rate: 0.9436571595919495\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S243.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199604 rows, 123647 columns, 731652 nonzeros\n",
      "S243.mps.gz rate: 0.9324933075610408\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S244.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199569 rows, 113561 columns, 668780 nonzeros\n",
      "S244.mps.gz rate: 1.0161939398208892\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S245.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199775 rows, 126249 columns, 762412 nonzeros\n",
      "S245.mps.gz rate: 0.9259479283004222\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S246.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199931 rows, 137490 columns, 832069 nonzeros\n",
      "S246.mps.gz rate: 0.8502436540839333\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S247.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199653 rows, 134172 columns, 793272 nonzeros\n",
      "S247.mps.gz rate: 0.8653072176012879\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S248.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199942 rows, 133980 columns, 813314 nonzeros\n",
      "S248.mps.gz rate: 0.8784893267651889\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S249.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199834 rows, 119002 columns, 713406 nonzeros\n",
      "S249.mps.gz rate: 0.9739332112065343\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S250.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199876 rows, 130757 columns, 795752 nonzeros\n",
      "S250.mps.gz rate: 0.8963191263182851\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S251.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199851 rows, 155433 columns, 938147 nonzeros\n",
      "S251.mps.gz rate: 0.7668899139822303\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S252.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199961 rows, 153088 columns, 922487 nonzeros\n",
      "S252.mps.gz rate: 0.764266304347826\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S253.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199942 rows, 144452 columns, 875322 nonzeros\n",
      "S253.mps.gz rate: 0.8058040040982472\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S254.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199914 rows, 129988 columns, 789734 nonzeros\n",
      "S254.mps.gz rate: 0.900083084592424\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S255.mps.gz\n",
      "Reading time = 0.37 seconds\n",
      "(null): 200012 rows, 143771 columns, 875321 nonzeros\n",
      "S255.mps.gz rate: 0.8151852598924678\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S256.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199760 rows, 126085 columns, 757542 nonzeros\n",
      "S256.mps.gz rate: 0.931117896657017\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S257.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199916 rows, 135105 columns, 807881 nonzeros\n",
      "S257.mps.gz rate: 0.8645127863513563\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S258.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199676 rows, 128491 columns, 767129 nonzeros\n",
      "S258.mps.gz rate: 0.9152391996326592\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S259.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199618 rows, 106160 columns, 631248 nonzeros\n",
      "S259.mps.gz rate: 1.0860964581763377\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S260.mps.gz\n",
      "Reading time = 0.38 seconds\n",
      "(null): 199922 rows, 155289 columns, 943449 nonzeros\n",
      "S260.mps.gz rate: 0.766957092904198\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S261.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199873 rows, 124988 columns, 754508 nonzeros\n",
      "S261.mps.gz rate: 0.9224885589016546\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S262.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199913 rows, 140293 columns, 852291 nonzeros\n",
      "S262.mps.gz rate: 0.8346817018668073\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S263.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199679 rows, 123045 columns, 736451 nonzeros\n",
      "S263.mps.gz rate: 0.944369945954732\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S264.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199920 rows, 138334 columns, 834110 nonzeros\n",
      "S264.mps.gz rate: 0.8414417279916724\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S265.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199765 rows, 126387 columns, 758716 nonzeros\n",
      "S265.mps.gz rate: 0.9233544589237818\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S266.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199953 rows, 128798 columns, 786538 nonzeros\n",
      "S266.mps.gz rate: 0.9076227891737448\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S267.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199993 rows, 128665 columns, 779476 nonzeros\n",
      "S267.mps.gz rate: 0.9070065674425835\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S268.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199870 rows, 133826 columns, 812897 nonzeros\n",
      "S268.mps.gz rate: 0.8750168128764215\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S269.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199748 rows, 133618 columns, 805233 nonzeros\n",
      "S269.mps.gz rate: 0.8711401158526546\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S270.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199678 rows, 127429 columns, 755211 nonzeros\n",
      "S270.mps.gz rate: 0.9095260890378172\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S271.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199969 rows, 126661 columns, 768589 nonzeros\n",
      "S271.mps.gz rate: 0.9181989720592764\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S272.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199822 rows, 126656 columns, 767293 nonzeros\n",
      "S272.mps.gz rate: 0.9174456796361798\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S273.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199824 rows, 112413 columns, 667055 nonzeros\n",
      "S273.mps.gz rate: 1.0319091208312208\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S274.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199952 rows, 117712 columns, 709965 nonzeros\n",
      "S274.mps.gz rate: 0.9939513388609487\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S275.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199866 rows, 114023 columns, 680905 nonzeros\n",
      "S275.mps.gz rate: 1.0015523183919035\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S276.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199915 rows, 131590 columns, 801430 nonzeros\n",
      "S276.mps.gz rate: 0.8914051219697546\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S277.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199771 rows, 137133 columns, 823442 nonzeros\n",
      "S277.mps.gz rate: 0.8575616372426768\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S278.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199626 rows, 128886 columns, 776777 nonzeros\n",
      "S278.mps.gz rate: 0.9085548469189827\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S279.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199639 rows, 115186 columns, 689165 nonzeros\n",
      "S279.mps.gz rate: 0.9957807372423731\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S280.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 200004 rows, 132640 columns, 808764 nonzeros\n",
      "S280.mps.gz rate: 0.8737937273823885\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S281.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199949 rows, 139336 columns, 848596 nonzeros\n",
      "S281.mps.gz rate: 0.8475914336567721\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S282.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199803 rows, 129586 columns, 775276 nonzeros\n",
      "S282.mps.gz rate: 0.8912999861096106\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S283.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199881 rows, 148783 columns, 891061 nonzeros\n",
      "S283.mps.gz rate: 0.7904128831923003\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S284.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199793 rows, 125632 columns, 750066 nonzeros\n",
      "S284.mps.gz rate: 0.9209437086092715\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S285.mps.gz\n",
      "Reading time = 0.37 seconds\n",
      "(null): 199962 rows, 147675 columns, 898211 nonzeros\n",
      "S285.mps.gz rate: 0.7943118334179787\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S286.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199944 rows, 142657 columns, 866964 nonzeros\n",
      "S286.mps.gz rate: 0.8271588495482171\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S287.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199800 rows, 110970 columns, 663424 nonzeros\n",
      "S287.mps.gz rate: 1.0444264215553754\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S288.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199793 rows, 136923 columns, 829703 nonzeros\n",
      "S288.mps.gz rate: 0.8544948620757652\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S289.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200109 rows, 136308 columns, 839025 nonzeros\n",
      "S289.mps.gz rate: 0.8605511048507791\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S290.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200070 rows, 139871 columns, 850980 nonzeros\n",
      "S290.mps.gz rate: 0.8357701024515446\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S291.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199854 rows, 143081 columns, 866891 nonzeros\n",
      "S291.mps.gz rate: 0.8275033023252563\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S292.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199836 rows, 136889 columns, 827528 nonzeros\n",
      "S292.mps.gz rate: 0.8642038439903864\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S293.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199930 rows, 131441 columns, 798777 nonzeros\n",
      "S293.mps.gz rate: 0.8817644418408259\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S294.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199794 rows, 120184 columns, 723160 nonzeros\n",
      "S294.mps.gz rate: 0.963522598682021\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S295.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199903 rows, 139394 columns, 845527 nonzeros\n",
      "S295.mps.gz rate: 0.8414996341305939\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S296.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199745 rows, 129460 columns, 769351 nonzeros\n",
      "S296.mps.gz rate: 0.9145682063957981\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S297.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199678 rows, 114263 columns, 682504 nonzeros\n",
      "S297.mps.gz rate: 1.0108259016479526\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S298.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199879 rows, 127263 columns, 769910 nonzeros\n",
      "S298.mps.gz rate: 0.9185702050085256\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S299.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199871 rows, 124623 columns, 754743 nonzeros\n",
      "S299.mps.gz rate: 0.9332145751586786\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S300.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199895 rows, 122724 columns, 752078 nonzeros\n",
      "S300.mps.gz rate: 0.9541735927772889\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S301.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199662 rows, 121730 columns, 729816 nonzeros\n",
      "S301.mps.gz rate: 0.9619650045181959\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S302.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199985 rows, 128466 columns, 788370 nonzeros\n",
      "S302.mps.gz rate: 0.908411564149269\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S303.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199905 rows, 138100 columns, 839791 nonzeros\n",
      "S303.mps.gz rate: 0.8435916002896452\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S304.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199907 rows, 136777 columns, 835176 nonzeros\n",
      "S304.mps.gz rate: 0.8583314446142261\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S305.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200021 rows, 132881 columns, 823146 nonzeros\n",
      "S305.mps.gz rate: 0.8834972644697134\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S306.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199847 rows, 147103 columns, 891223 nonzeros\n",
      "S306.mps.gz rate: 0.8069176019523736\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S307.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199952 rows, 129381 columns, 785777 nonzeros\n",
      "S307.mps.gz rate: 0.900441332189425\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S308.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199652 rows, 121057 columns, 726815 nonzeros\n",
      "S308.mps.gz rate: 0.9763995473206836\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S309.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199836 rows, 138059 columns, 831813 nonzeros\n",
      "S309.mps.gz rate: 0.8481880934962589\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S310.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199867 rows, 131012 columns, 794761 nonzeros\n",
      "S310.mps.gz rate: 0.8915213873538302\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S311.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199844 rows, 125746 columns, 762472 nonzeros\n",
      "S311.mps.gz rate: 0.9232898064351948\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S312.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199965 rows, 135269 columns, 831016 nonzeros\n",
      "S312.mps.gz rate: 0.864203919597247\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S313.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199841 rows, 142139 columns, 856686 nonzeros\n",
      "S313.mps.gz rate: 0.8280626710473551\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S314.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199919 rows, 121281 columns, 730009 nonzeros\n",
      "S314.mps.gz rate: 0.9605791508975025\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S315.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199898 rows, 112384 columns, 678034 nonzeros\n",
      "S315.mps.gz rate: 1.0339550113895215\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S316.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199895 rows, 125476 columns, 758699 nonzeros\n",
      "S316.mps.gz rate: 0.920494755969269\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S317.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199736 rows, 115711 columns, 691386 nonzeros\n",
      "S317.mps.gz rate: 1.008547156277277\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S318.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199900 rows, 131504 columns, 797224 nonzeros\n",
      "S318.mps.gz rate: 0.9003528409782212\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S319.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199870 rows, 150701 columns, 909780 nonzeros\n",
      "S319.mps.gz rate: 0.7883159368550972\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S320.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200024 rows, 128397 columns, 778009 nonzeros\n",
      "S320.mps.gz rate: 0.90344789987305\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S321.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199873 rows, 123967 columns, 753374 nonzeros\n",
      "S321.mps.gz rate: 0.9429928932699831\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S322.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200041 rows, 142412 columns, 867357 nonzeros\n",
      "S322.mps.gz rate: 0.8194534168468949\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S323.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199458 rows, 110993 columns, 647912 nonzeros\n",
      "S323.mps.gz rate: 1.0514176569693583\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S324.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199962 rows, 136262 columns, 823343 nonzeros\n",
      "S324.mps.gz rate: 0.8564383320368114\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S325.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199696 rows, 119135 columns, 715538 nonzeros\n",
      "S325.mps.gz rate: 0.9812397700088136\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S326.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199766 rows, 118578 columns, 713815 nonzeros\n",
      "S326.mps.gz rate: 0.9706690954477222\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S327.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200024 rows, 141401 columns, 866307 nonzeros\n",
      "S327.mps.gz rate: 0.8337989123132085\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S328.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199901 rows, 130525 columns, 798310 nonzeros\n",
      "S328.mps.gz rate: 0.9063397816510247\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S329.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199985 rows, 137315 columns, 830977 nonzeros\n",
      "S329.mps.gz rate: 0.8476859774969959\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S330.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199951 rows, 132637 columns, 800134 nonzeros\n",
      "S330.mps.gz rate: 0.882860740215777\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S331.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199614 rows, 122158 columns, 732385 nonzeros\n",
      "S331.mps.gz rate: 0.9577759950228393\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S332.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199768 rows, 122255 columns, 732693 nonzeros\n",
      "S332.mps.gz rate: 0.9611058852398675\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S333.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199625 rows, 105065 columns, 619407 nonzeros\n",
      "S333.mps.gz rate: 1.1059820111359635\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S334.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199859 rows, 135933 columns, 824714 nonzeros\n",
      "S334.mps.gz rate: 0.8607181479111032\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S335.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199958 rows, 117502 columns, 708465 nonzeros\n",
      "S335.mps.gz rate: 0.9659410052594849\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S336.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199834 rows, 124444 columns, 751779 nonzeros\n",
      "S336.mps.gz rate: 0.9425926521166148\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S337.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199980 rows, 120597 columns, 733003 nonzeros\n",
      "S337.mps.gz rate: 0.957735267046444\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S338.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199685 rows, 104234 columns, 611994 nonzeros\n",
      "S338.mps.gz rate: 1.117677533242512\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S339.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199706 rows, 142867 columns, 852383 nonzeros\n",
      "S339.mps.gz rate: 0.8287428167456445\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S340.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199844 rows, 133250 columns, 809979 nonzeros\n",
      "S340.mps.gz rate: 0.8840525328330207\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S341.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199846 rows, 123718 columns, 742076 nonzeros\n",
      "S341.mps.gz rate: 0.9351913222004882\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S342.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199981 rows, 133867 columns, 813210 nonzeros\n",
      "S342.mps.gz rate: 0.861302636198615\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S343.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199791 rows, 129836 columns, 784071 nonzeros\n",
      "S343.mps.gz rate: 0.9003666163467758\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S344.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199676 rows, 110793 columns, 657987 nonzeros\n",
      "S344.mps.gz rate: 1.047900138095367\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S345.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199935 rows, 136012 columns, 832482 nonzeros\n",
      "S345.mps.gz rate: 0.861688674528718\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S346.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199881 rows, 123676 columns, 755294 nonzeros\n",
      "S346.mps.gz rate: 0.951680196642841\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S347.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199818 rows, 134173 columns, 805012 nonzeros\n",
      "S347.mps.gz rate: 0.8690273005746313\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S348.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199871 rows, 123402 columns, 747346 nonzeros\n",
      "S348.mps.gz rate: 0.9448793374499603\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S349.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199588 rows, 128511 columns, 756623 nonzeros\n",
      "S349.mps.gz rate: 0.9174311926605505\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S350.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199731 rows, 124198 columns, 744908 nonzeros\n",
      "S350.mps.gz rate: 0.9396286574663038\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S351.mps.gz\n",
      "Reading time = 0.38 seconds\n",
      "(null): 199830 rows, 142921 columns, 865755 nonzeros\n",
      "S351.mps.gz rate: 0.8284296919277083\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S352.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199950 rows, 130265 columns, 790004 nonzeros\n",
      "S352.mps.gz rate: 0.8943307872413925\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S353.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200003 rows, 139513 columns, 851752 nonzeros\n",
      "S353.mps.gz rate: 0.8357644090514862\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S354.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199815 rows, 130489 columns, 798097 nonzeros\n",
      "S354.mps.gz rate: 0.9058234793737404\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S355.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199694 rows, 131236 columns, 784926 nonzeros\n",
      "S355.mps.gz rate: 0.8968575695693254\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S356.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199877 rows, 139222 columns, 844729 nonzeros\n",
      "S356.mps.gz rate: 0.8346382037321687\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S357.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199866 rows, 146239 columns, 880459 nonzeros\n",
      "S357.mps.gz rate: 0.7959573027714905\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S358.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199848 rows, 127644 columns, 776474 nonzeros\n",
      "S358.mps.gz rate: 0.9126946820845477\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S359.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199585 rows, 112415 columns, 666584 nonzeros\n",
      "S359.mps.gz rate: 1.0256638348974783\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S360.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199972 rows, 141447 columns, 866314 nonzeros\n",
      "S360.mps.gz rate: 0.838476602543709\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S361.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199570 rows, 115110 columns, 686197 nonzeros\n",
      "S361.mps.gz rate: 1.019025280166797\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S362.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199861 rows, 140323 columns, 850244 nonzeros\n",
      "S362.mps.gz rate: 0.8223883468854001\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S363.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199880 rows, 130884 columns, 792627 nonzeros\n",
      "S363.mps.gz rate: 0.895449405580514\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S364.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199804 rows, 127840 columns, 764973 nonzeros\n",
      "S364.mps.gz rate: 0.9066020025031288\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S365.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199894 rows, 127016 columns, 767032 nonzeros\n",
      "S365.mps.gz rate: 0.9258676072305851\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S366.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199985 rows, 125151 columns, 762684 nonzeros\n",
      "S366.mps.gz rate: 0.9276793633290984\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S367.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199805 rows, 124303 columns, 746827 nonzeros\n",
      "S367.mps.gz rate: 0.9388349436457688\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S368.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200019 rows, 128262 columns, 784760 nonzeros\n",
      "S368.mps.gz rate: 0.9082970794155713\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S369.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199708 rows, 111360 columns, 660510 nonzeros\n",
      "S369.mps.gz rate: 1.0353807471264367\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S370.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199822 rows, 130572 columns, 789709 nonzeros\n",
      "S370.mps.gz rate: 0.889930459822933\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S371.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199626 rows, 115196 columns, 682143 nonzeros\n",
      "S371.mps.gz rate: 1.0052432376124172\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S372.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199626 rows, 118478 columns, 708145 nonzeros\n",
      "S372.mps.gz rate: 0.9841489559243067\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S373.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199933 rows, 132616 columns, 804152 nonzeros\n",
      "S373.mps.gz rate: 0.8694275200579116\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S374.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199955 rows, 126172 columns, 764672 nonzeros\n",
      "S374.mps.gz rate: 0.9177947563643281\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S375.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199888 rows, 131116 columns, 796329 nonzeros\n",
      "S375.mps.gz rate: 0.8908142408249183\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S376.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199901 rows, 120366 columns, 726262 nonzeros\n",
      "S376.mps.gz rate: 0.9529269062692123\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S377.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199891 rows, 130735 columns, 791349 nonzeros\n",
      "S377.mps.gz rate: 0.8957050522048418\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S378.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199784 rows, 117234 columns, 707997 nonzeros\n",
      "S378.mps.gz rate: 1.0167698790453281\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S379.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199967 rows, 139478 columns, 852559 nonzeros\n",
      "S379.mps.gz rate: 0.8431437215905018\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S380.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199782 rows, 142176 columns, 859619 nonzeros\n",
      "S380.mps.gz rate: 0.8285505289218996\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S381.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199922 rows, 138065 columns, 836595 nonzeros\n",
      "S381.mps.gz rate: 0.8524970122768261\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S382.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199921 rows, 145083 columns, 873933 nonzeros\n",
      "S382.mps.gz rate: 0.8119490222837962\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S383.mps.gz\n",
      "Reading time = 0.27 seconds\n",
      "(null): 199631 rows, 108215 columns, 639948 nonzeros\n",
      "S383.mps.gz rate: 1.0710160328974725\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S384.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199897 rows, 138300 columns, 825105 nonzeros\n",
      "S384.mps.gz rate: 0.8430947216196675\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S385.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199876 rows, 123322 columns, 747293 nonzeros\n",
      "S385.mps.gz rate: 0.9390052058837839\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S386.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199885 rows, 123614 columns, 749714 nonzeros\n",
      "S386.mps.gz rate: 0.9497306130373582\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S387.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199990 rows, 136336 columns, 827376 nonzeros\n",
      "S387.mps.gz rate: 0.8471716934632086\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S388.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199925 rows, 132643 columns, 800549 nonzeros\n",
      "S388.mps.gz rate: 0.873773964702246\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S389.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199820 rows, 122942 columns, 734440 nonzeros\n",
      "S389.mps.gz rate: 0.9476013079338226\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S390.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199753 rows, 115993 columns, 694104 nonzeros\n",
      "S390.mps.gz rate: 1.0060951953997224\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S391.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199897 rows, 134714 columns, 812541 nonzeros\n",
      "S391.mps.gz rate: 0.867021987321288\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S392.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200006 rows, 147093 columns, 889612 nonzeros\n",
      "S392.mps.gz rate: 0.7933756195060269\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S393.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199826 rows, 132202 columns, 799717 nonzeros\n",
      "S393.mps.gz rate: 0.8910606496119574\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S394.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199873 rows, 130746 columns, 798166 nonzeros\n",
      "S394.mps.gz rate: 0.8994539029874719\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S395.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199943 rows, 148166 columns, 902595 nonzeros\n",
      "S395.mps.gz rate: 0.8011284640200856\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S396.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199816 rows, 123535 columns, 745840 nonzeros\n",
      "S396.mps.gz rate: 0.9406241146233861\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S397.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199939 rows, 125551 columns, 760690 nonzeros\n",
      "S397.mps.gz rate: 0.9287062627936058\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S398.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199767 rows, 129658 columns, 777545 nonzeros\n",
      "S398.mps.gz rate: 0.8938900800567646\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S399.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199934 rows, 129824 columns, 780349 nonzeros\n",
      "S399.mps.gz rate: 0.9050714813901899\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S400.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199874 rows, 125966 columns, 758179 nonzeros\n",
      "S400.mps.gz rate: 0.9319975231411651\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S401.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199903 rows, 129747 columns, 784401 nonzeros\n",
      "S401.mps.gz rate: 0.9110037226294251\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S402.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199753 rows, 130108 columns, 783916 nonzeros\n",
      "S402.mps.gz rate: 0.9007901128293418\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S403.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199790 rows, 131269 columns, 782344 nonzeros\n",
      "S403.mps.gz rate: 0.8920613396917779\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S404.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200045 rows, 132267 columns, 805368 nonzeros\n",
      "S404.mps.gz rate: 0.8853304301148436\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S405.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199991 rows, 149954 columns, 900482 nonzeros\n",
      "S405.mps.gz rate: 0.7675687210744628\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S406.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199898 rows, 133047 columns, 814947 nonzeros\n",
      "S406.mps.gz rate: 0.8884078558704819\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S407.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199935 rows, 135006 columns, 823350 nonzeros\n",
      "S407.mps.gz rate: 0.8577396560152881\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S408.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199969 rows, 135288 columns, 820355 nonzeros\n",
      "S408.mps.gz rate: 0.861125894388268\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S409.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199845 rows, 116271 columns, 705999 nonzeros\n",
      "S409.mps.gz rate: 0.9907887607399954\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S410.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199982 rows, 130349 columns, 798148 nonzeros\n",
      "S410.mps.gz rate: 0.8906857743442603\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S411.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199841 rows, 146611 columns, 889487 nonzeros\n",
      "S411.mps.gz rate: 0.8021226238140385\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S412.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199899 rows, 124808 columns, 758282 nonzeros\n",
      "S412.mps.gz rate: 0.9374399076982245\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S413.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200021 rows, 129901 columns, 796703 nonzeros\n",
      "S413.mps.gz rate: 0.8952971878584461\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S414.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200009 rows, 139159 columns, 850684 nonzeros\n",
      "S414.mps.gz rate: 0.8436392903082086\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S415.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199738 rows, 126770 columns, 756300 nonzeros\n",
      "S415.mps.gz rate: 0.9205648023980437\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S416.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199885 rows, 126405 columns, 760309 nonzeros\n",
      "S416.mps.gz rate: 0.9248051896681302\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S417.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199834 rows, 137308 columns, 829146 nonzeros\n",
      "S417.mps.gz rate: 0.8608384070848021\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S418.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199844 rows, 135413 columns, 814830 nonzeros\n",
      "S418.mps.gz rate: 0.8669773212320826\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S419.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199746 rows, 132095 columns, 798535 nonzeros\n",
      "S419.mps.gz rate: 0.8910253983875241\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S420.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199837 rows, 135762 columns, 825978 nonzeros\n",
      "S420.mps.gz rate: 0.8662217704512307\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S421.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199667 rows, 127538 columns, 760803 nonzeros\n",
      "S421.mps.gz rate: 0.9165895654628424\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S422.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199994 rows, 152429 columns, 922595 nonzeros\n",
      "S422.mps.gz rate: 0.7754429931312282\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S423.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199668 rows, 114905 columns, 681643 nonzeros\n",
      "S423.mps.gz rate: 1.0156216004525478\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S424.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199829 rows, 136405 columns, 819267 nonzeros\n",
      "S424.mps.gz rate: 0.849675598401818\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S425.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199888 rows, 124870 columns, 757441 nonzeros\n",
      "S425.mps.gz rate: 0.9313686233683031\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S426.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199960 rows, 141060 columns, 856949 nonzeros\n",
      "S426.mps.gz rate: 0.8351056288104352\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S427.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199935 rows, 133495 columns, 807908 nonzeros\n",
      "S427.mps.gz rate: 0.8756882280235214\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S428.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199682 rows, 116196 columns, 692553 nonzeros\n",
      "S428.mps.gz rate: 0.9931495060070915\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S429.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199926 rows, 133661 columns, 817161 nonzeros\n",
      "S429.mps.gz rate: 0.8835786055767951\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S430.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200015 rows, 149508 columns, 905476 nonzeros\n",
      "S430.mps.gz rate: 0.7818979586376649\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S431.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199827 rows, 114028 columns, 677548 nonzeros\n",
      "S431.mps.gz rate: 1.0137860876276001\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S432.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199931 rows, 128231 columns, 771269 nonzeros\n",
      "S432.mps.gz rate: 0.9163150876153192\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S433.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199604 rows, 123250 columns, 731386 nonzeros\n",
      "S433.mps.gz rate: 0.9452332657200812\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S434.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199816 rows, 120729 columns, 721327 nonzeros\n",
      "S434.mps.gz rate: 0.9583447224776152\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S435.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199837 rows, 126291 columns, 762688 nonzeros\n",
      "S435.mps.gz rate: 0.9200972357491825\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S436.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199729 rows, 128109 columns, 767837 nonzeros\n",
      "S436.mps.gz rate: 0.9148459514944305\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S437.mps.gz\n",
      "Reading time = 0.37 seconds\n",
      "(null): 200008 rows, 148812 columns, 905850 nonzeros\n",
      "S437.mps.gz rate: 0.7902588500927346\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S438.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199693 rows, 119127 columns, 714971 nonzeros\n",
      "S438.mps.gz rate: 0.9888606277334273\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S439.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199800 rows, 121381 columns, 729481 nonzeros\n",
      "S439.mps.gz rate: 0.9573162191776308\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S440.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199845 rows, 124782 columns, 749926 nonzeros\n",
      "S440.mps.gz rate: 0.9256142712891282\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S441.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199832 rows, 120837 columns, 726897 nonzeros\n",
      "S441.mps.gz rate: 0.9508676978077906\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S442.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 200173 rows, 155634 columns, 955234 nonzeros\n",
      "S442.mps.gz rate: 0.7524062865440714\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S443.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199640 rows, 123685 columns, 740079 nonzeros\n",
      "S443.mps.gz rate: 0.9540364635970409\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S444.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199788 rows, 120161 columns, 718471 nonzeros\n",
      "S444.mps.gz rate: 0.9770224948194507\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S445.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199813 rows, 120690 columns, 719414 nonzeros\n",
      "S445.mps.gz rate: 0.960311541967023\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S446.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199938 rows, 130548 columns, 782987 nonzeros\n",
      "S446.mps.gz rate: 0.8809020436927414\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S447.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199857 rows, 127907 columns, 768948 nonzeros\n",
      "S447.mps.gz rate: 0.9186361966116006\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S448.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199685 rows, 119224 columns, 708890 nonzeros\n",
      "S448.mps.gz rate: 0.960377105280816\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S449.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199669 rows, 137399 columns, 817691 nonzeros\n",
      "S449.mps.gz rate: 0.8660907284623616\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S450.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199973 rows, 139090 columns, 850355 nonzeros\n",
      "S450.mps.gz rate: 0.8390250916672658\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S451.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199900 rows, 122389 columns, 741786 nonzeros\n",
      "S451.mps.gz rate: 0.9706754692006634\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S452.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199885 rows, 140939 columns, 857397 nonzeros\n",
      "S452.mps.gz rate: 0.8443369117135783\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S453.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199760 rows, 124895 columns, 749774 nonzeros\n",
      "S453.mps.gz rate: 0.9255774850874735\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S454.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199905 rows, 140844 columns, 859033 nonzeros\n",
      "S454.mps.gz rate: 0.8370963619323506\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S455.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199937 rows, 125506 columns, 758445 nonzeros\n",
      "S455.mps.gz rate: 0.9210715025576466\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S456.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200000 rows, 138440 columns, 838976 nonzeros\n",
      "S456.mps.gz rate: 0.8386304536261195\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S457.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199989 rows, 138957 columns, 838739 nonzeros\n",
      "S457.mps.gz rate: 0.839108501191016\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S458.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199833 rows, 126599 columns, 759517 nonzeros\n",
      "S458.mps.gz rate: 0.9091698986563874\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S459.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199811 rows, 131636 columns, 783626 nonzeros\n",
      "S459.mps.gz rate: 0.891093621805585\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S460.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200063 rows, 144596 columns, 884779 nonzeros\n",
      "S460.mps.gz rate: 0.8070762676699218\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S461.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200066 rows, 148708 columns, 898875 nonzeros\n",
      "S461.mps.gz rate: 0.794173817145009\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S462.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199938 rows, 136836 columns, 835296 nonzeros\n",
      "S462.mps.gz rate: 0.8703849864070858\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S463.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199929 rows, 123275 columns, 755371 nonzeros\n",
      "S463.mps.gz rate: 0.9426079902656661\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S464.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199946 rows, 135906 columns, 824824 nonzeros\n",
      "S464.mps.gz rate: 0.8697187762129707\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S465.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199898 rows, 130497 columns, 793432 nonzeros\n",
      "S465.mps.gz rate: 0.9011701418423412\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S466.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199899 rows, 136906 columns, 819717 nonzeros\n",
      "S466.mps.gz rate: 0.8502183980249222\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S467.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199819 rows, 137995 columns, 827335 nonzeros\n",
      "S467.mps.gz rate: 0.8442334867205333\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S468.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199860 rows, 133538 columns, 795579 nonzeros\n",
      "S468.mps.gz rate: 0.8626757926582694\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S469.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199743 rows, 112427 columns, 675400 nonzeros\n",
      "S469.mps.gz rate: 1.0388963505207824\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S470.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199910 rows, 128550 columns, 776306 nonzeros\n",
      "S470.mps.gz rate: 0.9031505250875146\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S471.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200004 rows, 127151 columns, 777617 nonzeros\n",
      "S471.mps.gz rate: 0.9201657871349812\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S472.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199741 rows, 116233 columns, 699570 nonzeros\n",
      "S472.mps.gz rate: 1.0091798370514398\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S473.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200049 rows, 129331 columns, 786884 nonzeros\n",
      "S473.mps.gz rate: 0.9046554963620477\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S474.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199759 rows, 119911 columns, 722831 nonzeros\n",
      "S474.mps.gz rate: 0.9790594691062539\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S475.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199461 rows, 112451 columns, 658663 nonzeros\n",
      "S475.mps.gz rate: 1.0386746227245645\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S476.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199910 rows, 113429 columns, 687264 nonzeros\n",
      "S476.mps.gz rate: 1.0120868560950023\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S477.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199917 rows, 137227 columns, 829864 nonzeros\n",
      "S477.mps.gz rate: 0.847500856245491\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S478.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199953 rows, 123242 columns, 743108 nonzeros\n",
      "S478.mps.gz rate: 0.9436718001979846\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S479.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199807 rows, 128345 columns, 769683 nonzeros\n",
      "S479.mps.gz rate: 0.9108262885192255\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S480.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199993 rows, 141862 columns, 866569 nonzeros\n",
      "S480.mps.gz rate: 0.8324991893530331\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S481.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199912 rows, 131537 columns, 795537 nonzeros\n",
      "S481.mps.gz rate: 0.8872028402654766\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S482.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199796 rows, 119468 columns, 723033 nonzeros\n",
      "S482.mps.gz rate: 0.9659490407473131\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S483.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199756 rows, 126912 columns, 754888 nonzeros\n",
      "S483.mps.gz rate: 0.9250504286434695\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S484.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200008 rows, 135589 columns, 833092 nonzeros\n",
      "S484.mps.gz rate: 0.8688020414635406\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S485.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199848 rows, 136924 columns, 831961 nonzeros\n",
      "S485.mps.gz rate: 0.8610616108206012\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S486.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199632 rows, 116894 columns, 693548 nonzeros\n",
      "S486.mps.gz rate: 0.9786644310229782\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S487.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199772 rows, 123097 columns, 739965 nonzeros\n",
      "S487.mps.gz rate: 0.9480328521409944\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S488.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199841 rows, 135753 columns, 825549 nonzeros\n",
      "S488.mps.gz rate: 0.8699623581062665\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S489.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199833 rows, 125479 columns, 747894 nonzeros\n",
      "S489.mps.gz rate: 0.9172849640178835\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S490.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199877 rows, 120508 columns, 725036 nonzeros\n",
      "S490.mps.gz rate: 0.9576127725960103\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S491.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199857 rows, 119029 columns, 721303 nonzeros\n",
      "S491.mps.gz rate: 0.9585899234640297\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S492.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199880 rows, 121173 columns, 726127 nonzeros\n",
      "S492.mps.gz rate: 0.9564837051158261\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S493.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199788 rows, 119948 columns, 728699 nonzeros\n",
      "S493.mps.gz rate: 0.9704205155567411\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S494.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199945 rows, 134882 columns, 821708 nonzeros\n",
      "S494.mps.gz rate: 0.8748387479426462\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S495.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199880 rows, 143381 columns, 869851 nonzeros\n",
      "S495.mps.gz rate: 0.816007699764962\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S496.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199752 rows, 115822 columns, 691343 nonzeros\n",
      "S496.mps.gz rate: 0.9989466595292777\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S497.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199815 rows, 120101 columns, 717542 nonzeros\n",
      "S497.mps.gz rate: 0.9600253120290423\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S498.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199987 rows, 125720 columns, 765315 nonzeros\n",
      "S498.mps.gz rate: 0.9218899140948139\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S499.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 200005 rows, 136239 columns, 822941 nonzeros\n",
      "S499.mps.gz rate: 0.8543809041463898\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S500.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200049 rows, 137157 columns, 849603 nonzeros\n",
      "S500.mps.gz rate: 0.8625152197846264\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S501.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199856 rows, 126681 columns, 768915 nonzeros\n",
      "S501.mps.gz rate: 0.9077920130090542\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S502.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200075 rows, 140449 columns, 867231 nonzeros\n",
      "S502.mps.gz rate: 0.8337546013143561\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S503.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199845 rows, 125987 columns, 756924 nonzeros\n",
      "S503.mps.gz rate: 0.9278735107590466\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S504.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200020 rows, 128937 columns, 786817 nonzeros\n",
      "S504.mps.gz rate: 0.902766467344517\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S505.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199718 rows, 119497 columns, 715991 nonzeros\n",
      "S505.mps.gz rate: 0.9774303957421525\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S506.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 200033 rows, 148039 columns, 899854 nonzeros\n",
      "S506.mps.gz rate: 0.7903322773053046\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S507.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199882 rows, 128906 columns, 781434 nonzeros\n",
      "S507.mps.gz rate: 0.8975532558608599\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S508.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199929 rows, 140739 columns, 847269 nonzeros\n",
      "S508.mps.gz rate: 0.8384314227044387\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S509.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199902 rows, 144662 columns, 879237 nonzeros\n",
      "S509.mps.gz rate: 0.8191508481840428\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S510.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199821 rows, 124524 columns, 749535 nonzeros\n",
      "S510.mps.gz rate: 0.9363656805113872\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S511.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199875 rows, 133614 columns, 810010 nonzeros\n",
      "S511.mps.gz rate: 0.8793988653883575\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S512.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199888 rows, 143231 columns, 860627 nonzeros\n",
      "S512.mps.gz rate: 0.8140695799093772\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S513.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199920 rows, 135854 columns, 815980 nonzeros\n",
      "S513.mps.gz rate: 0.8590104082323672\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S514.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199683 rows, 124464 columns, 739101 nonzeros\n",
      "S514.mps.gz rate: 0.9424411878133436\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S515.mps.gz\n",
      "Reading time = 0.37 seconds\n",
      "(null): 199900 rows, 149599 columns, 907266 nonzeros\n",
      "S515.mps.gz rate: 0.7947914090334829\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S516.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199917 rows, 114307 columns, 696277 nonzeros\n",
      "S516.mps.gz rate: 1.0139361543912446\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S517.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199663 rows, 119297 columns, 701489 nonzeros\n",
      "S517.mps.gz rate: 0.9849367544867013\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S518.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199788 rows, 116256 columns, 701639 nonzeros\n",
      "S518.mps.gz rate: 0.9986581337737407\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S519.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199596 rows, 127388 columns, 754917 nonzeros\n",
      "S519.mps.gz rate: 0.9160988476151599\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S520.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199561 rows, 114851 columns, 681652 nonzeros\n",
      "S520.mps.gz rate: 1.0134870397297369\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S521.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199758 rows, 118727 columns, 703066 nonzeros\n",
      "S521.mps.gz rate: 0.9643973148483497\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S522.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199664 rows, 122542 columns, 725791 nonzeros\n",
      "S522.mps.gz rate: 0.9555907362373717\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S523.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199653 rows, 130964 columns, 779781 nonzeros\n",
      "S523.mps.gz rate: 0.8849760239455117\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S524.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199967 rows, 141944 columns, 855827 nonzeros\n",
      "S524.mps.gz rate: 0.8284957448007665\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S525.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199956 rows, 147786 columns, 901306 nonzeros\n",
      "S525.mps.gz rate: 0.8025117399483037\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S526.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200064 rows, 126778 columns, 773630 nonzeros\n",
      "S526.mps.gz rate: 0.9118301282556911\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S527.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199865 rows, 119756 columns, 715851 nonzeros\n",
      "S527.mps.gz rate: 0.9719763519155618\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S528.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199937 rows, 132941 columns, 807823 nonzeros\n",
      "S528.mps.gz rate: 0.8838507307753063\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S529.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199752 rows, 127824 columns, 767063 nonzeros\n",
      "S529.mps.gz rate: 0.9168857178620603\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S530.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199846 rows, 122713 columns, 744504 nonzeros\n",
      "S530.mps.gz rate: 0.9412205715775834\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S531.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199809 rows, 127307 columns, 755577 nonzeros\n",
      "S531.mps.gz rate: 0.9103977000479155\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S532.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199945 rows, 135323 columns, 822724 nonzeros\n",
      "S532.mps.gz rate: 0.860164199729536\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S533.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199923 rows, 125105 columns, 760829 nonzeros\n",
      "S533.mps.gz rate: 0.9320171056312698\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S534.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199657 rows, 112162 columns, 663706 nonzeros\n",
      "S534.mps.gz rate: 1.042242470712006\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S535.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200059 rows, 147006 columns, 898463 nonzeros\n",
      "S535.mps.gz rate: 0.792484660490048\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S536.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199838 rows, 120323 columns, 726343 nonzeros\n",
      "S536.mps.gz rate: 0.9549296476982789\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S537.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199885 rows, 132086 columns, 794062 nonzeros\n",
      "S537.mps.gz rate: 0.8774586254410006\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S538.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199789 rows, 124727 columns, 749457 nonzeros\n",
      "S538.mps.gz rate: 0.9404539514299229\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S539.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199919 rows, 134102 columns, 815086 nonzeros\n",
      "S539.mps.gz rate: 0.8687417040760018\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S540.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199746 rows, 117486 columns, 704158 nonzeros\n",
      "S540.mps.gz rate: 0.9839470234751374\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S541.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199886 rows, 123572 columns, 743804 nonzeros\n",
      "S541.mps.gz rate: 0.9306315346518629\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S542.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 200020 rows, 147267 columns, 890184 nonzeros\n",
      "S542.mps.gz rate: 0.7904011081912444\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S543.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199650 rows, 108002 columns, 635713 nonzeros\n",
      "S543.mps.gz rate: 1.0814614544175107\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S544.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199648 rows, 128391 columns, 763961 nonzeros\n",
      "S544.mps.gz rate: 0.9214041482658442\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S545.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199907 rows, 132295 columns, 814546 nonzeros\n",
      "S545.mps.gz rate: 0.8798518462526929\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S546.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199870 rows, 129210 columns, 779834 nonzeros\n",
      "S546.mps.gz rate: 0.9000851327296648\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S547.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199871 rows, 131781 columns, 799617 nonzeros\n",
      "S547.mps.gz rate: 0.8908719769921308\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S548.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199815 rows, 131085 columns, 796115 nonzeros\n",
      "S548.mps.gz rate: 0.893313498874776\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S549.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199852 rows, 122549 columns, 745141 nonzeros\n",
      "S549.mps.gz rate: 0.9718561554969849\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S550.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199769 rows, 118032 columns, 706755 nonzeros\n",
      "S550.mps.gz rate: 0.9887149247661651\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S551.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199712 rows, 121914 columns, 730974 nonzeros\n",
      "S551.mps.gz rate: 0.9670751513361877\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S552.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199823 rows, 132043 columns, 793567 nonzeros\n",
      "S552.mps.gz rate: 0.8777443711518217\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S553.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199908 rows, 131052 columns, 798259 nonzeros\n",
      "S553.mps.gz rate: 0.8958276104141868\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S554.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199744 rows, 130678 columns, 780684 nonzeros\n",
      "S554.mps.gz rate: 0.8915043082997903\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S555.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199691 rows, 124186 columns, 743081 nonzeros\n",
      "S555.mps.gz rate: 0.9477718905512699\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S556.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199603 rows, 107230 columns, 637177 nonzeros\n",
      "S556.mps.gz rate: 1.079921663713513\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S557.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199797 rows, 132256 columns, 795112 nonzeros\n",
      "S557.mps.gz rate: 0.8801112992983304\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S558.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199963 rows, 134969 columns, 820329 nonzeros\n",
      "S558.mps.gz rate: 0.8631611703428195\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S559.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199999 rows, 134503 columns, 813443 nonzeros\n",
      "S559.mps.gz rate: 0.8810212411619072\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S560.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199844 rows, 129561 columns, 781389 nonzeros\n",
      "S560.mps.gz rate: 0.9092242264261622\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S561.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199849 rows, 111723 columns, 671346 nonzeros\n",
      "S561.mps.gz rate: 1.0284364007411186\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S562.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199804 rows, 127654 columns, 769226 nonzeros\n",
      "S562.mps.gz rate: 0.9087063468438121\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S563.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199961 rows, 134612 columns, 815840 nonzeros\n",
      "S563.mps.gz rate: 0.8676789587852495\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S564.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199853 rows, 131216 columns, 787378 nonzeros\n",
      "S564.mps.gz rate: 0.8855627362516766\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S565.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199799 rows, 129947 columns, 780353 nonzeros\n",
      "S565.mps.gz rate: 0.8949802611834056\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S566.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199727 rows, 128060 columns, 767012 nonzeros\n",
      "S566.mps.gz rate: 0.9167577697954085\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S567.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199702 rows, 119900 columns, 720560 nonzeros\n",
      "S567.mps.gz rate: 0.9724770642201834\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S568.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199728 rows, 133568 columns, 800063 nonzeros\n",
      "S568.mps.gz rate: 0.8916806420699568\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S569.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199860 rows, 139217 columns, 828330 nonzeros\n",
      "S569.mps.gz rate: 0.8411329076190408\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S570.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199785 rows, 124776 columns, 748214 nonzeros\n",
      "S570.mps.gz rate: 0.9352760146181959\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S571.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199912 rows, 122085 columns, 741108 nonzeros\n",
      "S571.mps.gz rate: 0.9575295900397265\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S572.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199827 rows, 130409 columns, 785353 nonzeros\n",
      "S572.mps.gz rate: 0.885675068438528\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S573.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199892 rows, 131343 columns, 788132 nonzeros\n",
      "S573.mps.gz rate: 0.886229186176652\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S574.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199698 rows, 115912 columns, 692598 nonzeros\n",
      "S574.mps.gz rate: 0.9955828559596936\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S575.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199825 rows, 133371 columns, 797637 nonzeros\n",
      "S575.mps.gz rate: 0.8742530235208554\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S576.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199843 rows, 129451 columns, 785923 nonzeros\n",
      "S576.mps.gz rate: 0.9007269159759291\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S577.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199901 rows, 137942 columns, 836066 nonzeros\n",
      "S577.mps.gz rate: 0.8532571660552987\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S578.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199863 rows, 142291 columns, 864276 nonzeros\n",
      "S578.mps.gz rate: 0.8243669662873969\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S579.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 200083 rows, 137872 columns, 838805 nonzeros\n",
      "S579.mps.gz rate: 0.8391841708251132\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S580.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199965 rows, 135011 columns, 816832 nonzeros\n",
      "S580.mps.gz rate: 0.8673367355252535\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S581.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199589 rows, 119577 columns, 708354 nonzeros\n",
      "S581.mps.gz rate: 0.9767764703914633\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S582.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199716 rows, 130723 columns, 789856 nonzeros\n",
      "S582.mps.gz rate: 0.9080268965675512\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S583.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199864 rows, 122739 columns, 742596 nonzeros\n",
      "S583.mps.gz rate: 0.948353823967932\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S584.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199865 rows, 127603 columns, 771761 nonzeros\n",
      "S584.mps.gz rate: 0.9114205778860999\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S585.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200004 rows, 145483 columns, 881600 nonzeros\n",
      "S585.mps.gz rate: 0.8055924059855791\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S586.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199879 rows, 134330 columns, 818541 nonzeros\n",
      "S586.mps.gz rate: 0.8680116131913943\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S587.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199867 rows, 127029 columns, 766272 nonzeros\n",
      "S587.mps.gz rate: 0.9139645277849939\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S588.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200056 rows, 140475 columns, 854619 nonzeros\n",
      "S588.mps.gz rate: 0.8385833778252358\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S589.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199822 rows, 130593 columns, 784408 nonzeros\n",
      "S589.mps.gz rate: 0.8989762085257249\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S590.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199985 rows, 130710 columns, 789880 nonzeros\n",
      "S590.mps.gz rate: 0.8897559482824573\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S591.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199714 rows, 121609 columns, 722366 nonzeros\n",
      "S591.mps.gz rate: 0.9703229201786052\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S592.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199823 rows, 134453 columns, 820360 nonzeros\n",
      "S592.mps.gz rate: 0.8813488728403233\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S593.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199854 rows, 126966 columns, 774282 nonzeros\n",
      "S593.mps.gz rate: 0.9262322196493549\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S594.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200018 rows, 134962 columns, 827491 nonzeros\n",
      "S594.mps.gz rate: 0.8639468887538715\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S595.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199765 rows, 120418 columns, 725891 nonzeros\n",
      "S595.mps.gz rate: 0.9691242173097044\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S596.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199640 rows, 124497 columns, 744599 nonzeros\n",
      "S596.mps.gz rate: 0.9478140035502864\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S597.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199947 rows, 142778 columns, 872973 nonzeros\n",
      "S597.mps.gz rate: 0.8348625138326633\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S598.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199877 rows, 140931 columns, 854679 nonzeros\n",
      "S598.mps.gz rate: 0.8365796027843413\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S599.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199778 rows, 125001 columns, 756101 nonzeros\n",
      "S599.mps.gz rate: 0.9391924864601083\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S600.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199878 rows, 136040 columns, 817502 nonzeros\n",
      "S600.mps.gz rate: 0.8622463981182006\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S601.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199870 rows, 135155 columns, 816805 nonzeros\n",
      "S601.mps.gz rate: 0.8641929636343457\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S602.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199953 rows, 145215 columns, 879748 nonzeros\n",
      "S602.mps.gz rate: 0.8091450607719588\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S603.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199799 rows, 126494 columns, 757452 nonzeros\n",
      "S603.mps.gz rate: 0.9265261593435261\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S604.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199959 rows, 137136 columns, 828044 nonzeros\n",
      "S604.mps.gz rate: 0.8502508458756272\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S605.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199776 rows, 133966 columns, 806917 nonzeros\n",
      "S605.mps.gz rate: 0.8778346744696415\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S606.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199848 rows, 134199 columns, 798976 nonzeros\n",
      "S606.mps.gz rate: 0.8807815259428163\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S607.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199898 rows, 139624 columns, 846819 nonzeros\n",
      "S607.mps.gz rate: 0.839397238297141\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S608.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200022 rows, 127323 columns, 774634 nonzeros\n",
      "S608.mps.gz rate: 0.9094978911901228\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S609.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199721 rows, 125583 columns, 744719 nonzeros\n",
      "S609.mps.gz rate: 0.9197104703662119\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S610.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199846 rows, 116601 columns, 703231 nonzeros\n",
      "S610.mps.gz rate: 0.9965609214329207\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S611.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199905 rows, 138366 columns, 843423 nonzeros\n",
      "S611.mps.gz rate: 0.8426925689837099\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S612.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199931 rows, 141177 columns, 857017 nonzeros\n",
      "S612.mps.gz rate: 0.8202469240740347\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S613.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199753 rows, 132569 columns, 795324 nonzeros\n",
      "S613.mps.gz rate: 0.8765246777150012\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S614.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200025 rows, 130183 columns, 798120 nonzeros\n",
      "S614.mps.gz rate: 0.8902852138912146\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S615.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199804 rows, 136656 columns, 820556 nonzeros\n",
      "S615.mps.gz rate: 0.8583596768528274\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S616.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199729 rows, 122526 columns, 737692 nonzeros\n",
      "S616.mps.gz rate: 0.9483701418474446\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S617.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199772 rows, 122854 columns, 735884 nonzeros\n",
      "S617.mps.gz rate: 0.9450241750370357\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S618.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200063 rows, 141405 columns, 870740 nonzeros\n",
      "S618.mps.gz rate: 0.830946571903398\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S619.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200127 rows, 150776 columns, 927639 nonzeros\n",
      "S619.mps.gz rate: 0.7806282166923117\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S620.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199826 rows, 121120 columns, 727761 nonzeros\n",
      "S620.mps.gz rate: 0.9560766182298546\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S621.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199888 rows, 135456 columns, 826714 nonzeros\n",
      "S621.mps.gz rate: 0.8652256083156155\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S622.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199580 rows, 114323 columns, 679585 nonzeros\n",
      "S622.mps.gz rate: 1.0181678227478286\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S623.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199936 rows, 133530 columns, 803991 nonzeros\n",
      "S623.mps.gz rate: 0.8769564891784617\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S624.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199803 rows, 126989 columns, 770393 nonzeros\n",
      "S624.mps.gz rate: 0.9197647040294828\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S625.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199961 rows, 136649 columns, 835604 nonzeros\n",
      "S625.mps.gz rate: 0.8598672511324635\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S626.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199988 rows, 138138 columns, 833102 nonzeros\n",
      "S626.mps.gz rate: 0.847703021616065\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S627.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199835 rows, 132924 columns, 793771 nonzeros\n",
      "S627.mps.gz rate: 0.875688363275255\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S628.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199605 rows, 116170 columns, 685662 nonzeros\n",
      "S628.mps.gz rate: 1.0088663166049754\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S629.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199867 rows, 129585 columns, 786912 nonzeros\n",
      "S629.mps.gz rate: 0.9059690550603852\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S630.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 200018 rows, 139381 columns, 850759 nonzeros\n",
      "S630.mps.gz rate: 0.8415781204037853\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S631.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199951 rows, 138292 columns, 840336 nonzeros\n",
      "S631.mps.gz rate: 0.8489283544962832\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S632.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199923 rows, 126366 columns, 765996 nonzeros\n",
      "S632.mps.gz rate: 0.9155943845654685\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S633.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199814 rows, 132774 columns, 806685 nonzeros\n",
      "S633.mps.gz rate: 0.8811966198201454\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S634.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199856 rows, 127316 columns, 770413 nonzeros\n",
      "S634.mps.gz rate: 0.9174023689088567\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S635.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199822 rows, 119278 columns, 715649 nonzeros\n",
      "S635.mps.gz rate: 0.9767098710575295\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S636.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199813 rows, 140026 columns, 846340 nonzeros\n",
      "S636.mps.gz rate: 0.845557253652893\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S637.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199905 rows, 133636 columns, 809224 nonzeros\n",
      "S637.mps.gz rate: 0.8837439013439492\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S638.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199700 rows, 120495 columns, 706875 nonzeros\n",
      "S638.mps.gz rate: 0.9660151873521723\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S639.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 200045 rows, 143328 columns, 868931 nonzeros\n",
      "S639.mps.gz rate: 0.8197979459700825\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S640.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199802 rows, 132708 columns, 799017 nonzeros\n",
      "S640.mps.gz rate: 0.874099526780601\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S641.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199990 rows, 135497 columns, 824011 nonzeros\n",
      "S641.mps.gz rate: 0.856845539015624\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S642.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199865 rows, 128208 columns, 761745 nonzeros\n",
      "S642.mps.gz rate: 0.9016598028204169\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S643.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199851 rows, 120417 columns, 734044 nonzeros\n",
      "S643.mps.gz rate: 0.969962712905985\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S644.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199801 rows, 140623 columns, 847929 nonzeros\n",
      "S644.mps.gz rate: 0.8412564089800388\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S645.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199552 rows, 113929 columns, 670697 nonzeros\n",
      "S645.mps.gz rate: 1.0251999052041183\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S646.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199963 rows, 138046 columns, 841862 nonzeros\n",
      "S646.mps.gz rate: 0.8547875345899193\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S647.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199972 rows, 136430 columns, 823900 nonzeros\n",
      "S647.mps.gz rate: 0.8531847834054094\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S648.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199867 rows, 119544 columns, 723011 nonzeros\n",
      "S648.mps.gz rate: 0.9737000602288697\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S649.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199869 rows, 142191 columns, 857246 nonzeros\n",
      "S649.mps.gz rate: 0.8256500059778747\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S650.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199925 rows, 121259 columns, 727213 nonzeros\n",
      "S650.mps.gz rate: 0.9558053422838717\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S651.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199904 rows, 131715 columns, 802062 nonzeros\n",
      "S651.mps.gz rate: 0.8958736666287058\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S652.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199706 rows, 126557 columns, 755631 nonzeros\n",
      "S652.mps.gz rate: 0.9308058819346223\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S653.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199854 rows, 120867 columns, 720923 nonzeros\n",
      "S653.mps.gz rate: 0.9663514441493543\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S654.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199942 rows, 126746 columns, 768570 nonzeros\n",
      "S654.mps.gz rate: 0.9246840136966847\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S655.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199613 rows, 116900 columns, 698311 nonzeros\n",
      "S655.mps.gz rate: 1.009409751924722\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S656.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199830 rows, 113957 columns, 677287 nonzeros\n",
      "S656.mps.gz rate: 1.0240704827259406\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S657.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199916 rows, 130495 columns, 791725 nonzeros\n",
      "S657.mps.gz rate: 0.8873903214682556\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S658.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199865 rows, 130771 columns, 786032 nonzeros\n",
      "S658.mps.gz rate: 0.8916349955265311\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S659.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199851 rows, 133089 columns, 795650 nonzeros\n",
      "S659.mps.gz rate: 0.8723485787705971\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S660.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199887 rows, 132602 columns, 808119 nonzeros\n",
      "S660.mps.gz rate: 0.886110315078204\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S661.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199792 rows, 110951 columns, 668884 nonzeros\n",
      "S661.mps.gz rate: 1.0473091725175978\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S662.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199957 rows, 133674 columns, 814310 nonzeros\n",
      "S662.mps.gz rate: 0.8790041444110297\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S663.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199938 rows, 142791 columns, 860664 nonzeros\n",
      "S663.mps.gz rate: 0.8207800211497923\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S664.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199910 rows, 138182 columns, 832114 nonzeros\n",
      "S664.mps.gz rate: 0.8496041452577036\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S665.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200038 rows, 143660 columns, 881225 nonzeros\n",
      "S665.mps.gz rate: 0.820687734929695\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S666.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199670 rows, 122657 columns, 734558 nonzeros\n",
      "S666.mps.gz rate: 0.9587712075136355\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S667.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199823 rows, 132328 columns, 796465 nonzeros\n",
      "S667.mps.gz rate: 0.8796324285109727\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S668.mps.gz\n",
      "Reading time = 0.27 seconds\n",
      "(null): 199592 rows, 106110 columns, 629628 nonzeros\n",
      "S668.mps.gz rate: 1.0866082367354633\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S669.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199743 rows, 125220 columns, 743417 nonzeros\n",
      "S669.mps.gz rate: 0.927966778469893\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S670.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199867 rows, 129090 columns, 775484 nonzeros\n",
      "S670.mps.gz rate: 0.9016964908203579\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S671.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199820 rows, 135554 columns, 820209 nonzeros\n",
      "S671.mps.gz rate: 0.858698378505983\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S672.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199752 rows, 128710 columns, 769975 nonzeros\n",
      "S672.mps.gz rate: 0.9129049801880196\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S673.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199857 rows, 123986 columns, 743167 nonzeros\n",
      "S673.mps.gz rate: 0.9307502459955156\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S674.mps.gz\n",
      "Reading time = 0.28 seconds\n",
      "(null): 199560 rows, 109498 columns, 643048 nonzeros\n",
      "S674.mps.gz rate: 1.0703391842773384\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S675.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199784 rows, 118890 columns, 702233 nonzeros\n",
      "S675.mps.gz rate: 0.9681217932542686\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S676.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199786 rows, 119909 columns, 718072 nonzeros\n",
      "S676.mps.gz rate: 0.957392689456171\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S677.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199848 rows, 137747 columns, 836410 nonzeros\n",
      "S677.mps.gz rate: 0.8443015092887686\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S678.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199835 rows, 126719 columns, 763573 nonzeros\n",
      "S678.mps.gz rate: 0.9154112642934367\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S679.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199669 rows, 123742 columns, 738841 nonzeros\n",
      "S679.mps.gz rate: 0.9414750044447319\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S680.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199694 rows, 114252 columns, 681413 nonzeros\n",
      "S680.mps.gz rate: 1.0214263207646255\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S681.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199761 rows, 134377 columns, 803641 nonzeros\n",
      "S681.mps.gz rate: 0.8647313156269302\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S682.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199992 rows, 133345 columns, 808845 nonzeros\n",
      "S682.mps.gz rate: 0.8864224380366718\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S683.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199908 rows, 120223 columns, 727300 nonzeros\n",
      "S683.mps.gz rate: 0.9690325478485813\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S684.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199969 rows, 148363 columns, 901500 nonzeros\n",
      "S684.mps.gz rate: 0.7960205711666656\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S685.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199946 rows, 139133 columns, 852385 nonzeros\n",
      "S685.mps.gz rate: 0.8502655732284935\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S686.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199807 rows, 137279 columns, 830463 nonzeros\n",
      "S686.mps.gz rate: 0.8515504920636077\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S687.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199755 rows, 124860 columns, 760050 nonzeros\n",
      "S687.mps.gz rate: 0.9466602594906295\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S688.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199878 rows, 135067 columns, 815081 nonzeros\n",
      "S688.mps.gz rate: 0.8647560099802319\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S689.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199734 rows, 132203 columns, 792334 nonzeros\n",
      "S689.mps.gz rate: 0.8955923844390824\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S690.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199934 rows, 135735 columns, 817897 nonzeros\n",
      "S690.mps.gz rate: 0.8516594835525104\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S691.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199853 rows, 134315 columns, 812331 nonzeros\n",
      "S691.mps.gz rate: 0.8658749953467595\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S692.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199763 rows, 128434 columns, 777196 nonzeros\n",
      "S692.mps.gz rate: 0.9101951196723609\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S693.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199895 rows, 138565 columns, 845083 nonzeros\n",
      "S693.mps.gz rate: 0.8515858983148703\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S694.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199890 rows, 139803 columns, 850302 nonzeros\n",
      "S694.mps.gz rate: 0.8511977568435584\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S695.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200043 rows, 135843 columns, 832985 nonzeros\n",
      "S695.mps.gz rate: 0.8539269597991799\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S696.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199765 rows, 146118 columns, 870437 nonzeros\n",
      "S696.mps.gz rate: 0.7959320549145211\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S697.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199808 rows, 126112 columns, 757109 nonzeros\n",
      "S697.mps.gz rate: 0.9325044404973356\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S698.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199982 rows, 124514 columns, 760703 nonzeros\n",
      "S698.mps.gz rate: 0.9364408821497984\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S699.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199887 rows, 142103 columns, 861820 nonzeros\n",
      "S699.mps.gz rate: 0.820531586243781\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S700.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199867 rows, 117720 columns, 705717 nonzeros\n",
      "S700.mps.gz rate: 0.9785932721712538\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S701.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199795 rows, 122104 columns, 739510 nonzeros\n",
      "S701.mps.gz rate: 0.9557426456135754\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S702.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199919 rows, 127607 columns, 778423 nonzeros\n",
      "S702.mps.gz rate: 0.9145266325515058\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S703.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199835 rows, 136938 columns, 828263 nonzeros\n",
      "S703.mps.gz rate: 0.8485592019746163\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S704.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199809 rows, 126705 columns, 762871 nonzeros\n",
      "S704.mps.gz rate: 0.9210370545755889\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S705.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199852 rows, 118553 columns, 718139 nonzeros\n",
      "S705.mps.gz rate: 0.9717172910006495\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S706.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199748 rows, 121419 columns, 723299 nonzeros\n",
      "S706.mps.gz rate: 0.9512514515850072\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S707.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199709 rows, 132414 columns, 790642 nonzeros\n",
      "S707.mps.gz rate: 0.8767955050070233\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S708.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199680 rows, 135001 columns, 803231 nonzeros\n",
      "S708.mps.gz rate: 0.8718453937378242\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S709.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199720 rows, 130179 columns, 778060 nonzeros\n",
      "S709.mps.gz rate: 0.8995306462639904\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S710.mps.gz\n",
      "Reading time = 0.36 seconds\n",
      "(null): 199974 rows, 141907 columns, 871193 nonzeros\n",
      "S710.mps.gz rate: 0.8251883275666458\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S711.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199976 rows, 128033 columns, 776831 nonzeros\n",
      "S711.mps.gz rate: 0.9013301258269352\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S712.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199909 rows, 138365 columns, 845901 nonzeros\n",
      "S712.mps.gz rate: 0.8585986340476276\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S713.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199774 rows, 121762 columns, 733223 nonzeros\n",
      "S713.mps.gz rate: 0.9551419983246003\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S714.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 200027 rows, 126841 columns, 773450 nonzeros\n",
      "S714.mps.gz rate: 0.9121656246797172\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S715.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199758 rows, 120551 columns, 718522 nonzeros\n",
      "S715.mps.gz rate: 0.9746912095295768\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S716.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199978 rows, 140148 columns, 850962 nonzeros\n",
      "S716.mps.gz rate: 0.8269829037874247\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S717.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199870 rows, 129045 columns, 780067 nonzeros\n",
      "S717.mps.gz rate: 0.9004610794684025\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S718.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199597 rows, 127565 columns, 758256 nonzeros\n",
      "S718.mps.gz rate: 0.9195312193783561\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S719.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199818 rows, 129634 columns, 781345 nonzeros\n",
      "S719.mps.gz rate: 0.8809417282503047\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S720.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200009 rows, 140708 columns, 858147 nonzeros\n",
      "S720.mps.gz rate: 0.8258236916166813\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S721.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199768 rows, 132570 columns, 802731 nonzeros\n",
      "S721.mps.gz rate: 0.8870785245530662\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S722.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199701 rows, 128038 columns, 777040 nonzeros\n",
      "S722.mps.gz rate: 0.9223824177197394\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S723.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199833 rows, 125416 columns, 764701 nonzeros\n",
      "S723.mps.gz rate: 0.9384767493780697\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S724.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199906 rows, 145036 columns, 880730 nonzeros\n",
      "S724.mps.gz rate: 0.8046278165420998\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S725.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199788 rows, 125482 columns, 743339 nonzeros\n",
      "S725.mps.gz rate: 0.9260292312841683\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S726.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200007 rows, 135653 columns, 821212 nonzeros\n",
      "S726.mps.gz rate: 0.85733452264233\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S727.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199818 rows, 126984 columns, 766123 nonzeros\n",
      "S727.mps.gz rate: 0.9119259119259119\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S728.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199651 rows, 110995 columns, 655097 nonzeros\n",
      "S728.mps.gz rate: 1.0441911797828731\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S729.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199896 rows, 129308 columns, 779115 nonzeros\n",
      "S729.mps.gz rate: 0.8854827234200514\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S730.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199743 rows, 130861 columns, 794516 nonzeros\n",
      "S730.mps.gz rate: 0.9009559761884748\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S731.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199886 rows, 133137 columns, 803143 nonzeros\n",
      "S731.mps.gz rate: 0.8870561902401286\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S732.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199868 rows, 131422 columns, 789631 nonzeros\n",
      "S732.mps.gz rate: 0.887979181567774\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S733.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199775 rows, 127439 columns, 761007 nonzeros\n",
      "S733.mps.gz rate: 0.9180863001122105\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S734.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199609 rows, 124968 columns, 741830 nonzeros\n",
      "S734.mps.gz rate: 0.9290378336854234\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S735.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199866 rows, 120463 columns, 721286 nonzeros\n",
      "S735.mps.gz rate: 0.9762333662618398\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S736.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199888 rows, 119504 columns, 727942 nonzeros\n",
      "S736.mps.gz rate: 0.9698420136564465\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S737.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199879 rows, 131609 columns, 800784 nonzeros\n",
      "S737.mps.gz rate: 0.8905166060071878\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S738.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199764 rows, 117518 columns, 707256 nonzeros\n",
      "S738.mps.gz rate: 0.9947412311305501\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S739.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199941 rows, 128097 columns, 778254 nonzeros\n",
      "S739.mps.gz rate: 0.9032217772469301\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S740.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199924 rows, 125920 columns, 768188 nonzeros\n",
      "S740.mps.gz rate: 0.9212198221092757\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S741.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199839 rows, 133624 columns, 810239 nonzeros\n",
      "S741.mps.gz rate: 0.8823265281685925\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S742.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199957 rows, 135428 columns, 829800 nonzeros\n",
      "S742.mps.gz rate: 0.8661428951177009\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S743.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200030 rows, 130467 columns, 796038 nonzeros\n",
      "S743.mps.gz rate: 0.8845148581633671\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S744.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199758 rows, 125245 columns, 753974 nonzeros\n",
      "S744.mps.gz rate: 0.9341690287037407\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S745.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199858 rows, 138842 columns, 839420 nonzeros\n",
      "S745.mps.gz rate: 0.8527678944411633\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S746.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199839 rows, 133058 columns, 803009 nonzeros\n",
      "S746.mps.gz rate: 0.8830735468742954\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S747.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199871 rows, 135459 columns, 817250 nonzeros\n",
      "S747.mps.gz rate: 0.8570859079130956\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S748.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 200025 rows, 136641 columns, 834361 nonzeros\n",
      "S748.mps.gz rate: 0.8555265257133657\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S749.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199881 rows, 125551 columns, 759897 nonzeros\n",
      "S749.mps.gz rate: 0.9374676426312814\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S750.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199683 rows, 117261 columns, 702897 nonzeros\n",
      "S750.mps.gz rate: 1.0037437852312363\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S751.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199922 rows, 131141 columns, 794613 nonzeros\n",
      "S751.mps.gz rate: 0.8875942687641546\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S752.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 200082 rows, 136259 columns, 837562 nonzeros\n",
      "S752.mps.gz rate: 0.8513199128130986\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S753.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199688 rows, 127434 columns, 755690 nonzeros\n",
      "S753.mps.gz rate: 0.9102751228086696\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S754.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199624 rows, 118565 columns, 702863 nonzeros\n",
      "S754.mps.gz rate: 0.9935478429553409\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S755.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199704 rows, 121986 columns, 727617 nonzeros\n",
      "S755.mps.gz rate: 0.9574869247290672\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S756.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199745 rows, 121079 columns, 724202 nonzeros\n",
      "S756.mps.gz rate: 0.9646594372269345\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S757.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199904 rows, 123135 columns, 737381 nonzeros\n",
      "S757.mps.gz rate: 0.9298737158403378\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S758.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199778 rows, 136599 columns, 814100 nonzeros\n",
      "S758.mps.gz rate: 0.8470047364914823\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S759.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199711 rows, 116157 columns, 698736 nonzeros\n",
      "S759.mps.gz rate: 0.9952047659633083\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S760.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199977 rows, 128783 columns, 784141 nonzeros\n",
      "S760.mps.gz rate: 0.9030695045153475\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S761.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199877 rows, 131004 columns, 794232 nonzeros\n",
      "S761.mps.gz rate: 0.8816524686269123\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S762.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199850 rows, 138638 columns, 844102 nonzeros\n",
      "S762.mps.gz rate: 0.8561866155022432\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S763.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199727 rows, 120431 columns, 722201 nonzeros\n",
      "S763.mps.gz rate: 0.9673589026081324\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S764.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199636 rows, 120593 columns, 718557 nonzeros\n",
      "S764.mps.gz rate: 0.9627424477374309\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S765.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199930 rows, 148394 columns, 906063 nonzeros\n",
      "S765.mps.gz rate: 0.7992236882892838\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S766.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199803 rows, 125732 columns, 763671 nonzeros\n",
      "S766.mps.gz rate: 0.9392994623484873\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S767.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199650 rows, 126066 columns, 757303 nonzeros\n",
      "S767.mps.gz rate: 0.9344311709739342\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S768.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199772 rows, 132917 columns, 797534 nonzeros\n",
      "S768.mps.gz rate: 0.8794962269687098\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S769.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199852 rows, 123059 columns, 737702 nonzeros\n",
      "S769.mps.gz rate: 0.945075126565306\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S770.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199905 rows, 122069 columns, 735778 nonzeros\n",
      "S770.mps.gz rate: 0.9527398438588013\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S771.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199828 rows, 140419 columns, 844222 nonzeros\n",
      "S771.mps.gz rate: 0.8410542732821057\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S772.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199891 rows, 145921 columns, 882687 nonzeros\n",
      "S772.mps.gz rate: 0.8011184133880661\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S773.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199594 rows, 123765 columns, 734397 nonzeros\n",
      "S773.mps.gz rate: 0.9518038217589788\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S774.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199903 rows, 153756 columns, 934018 nonzeros\n",
      "S774.mps.gz rate: 0.7681001066625042\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S775.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199715 rows, 108287 columns, 648770 nonzeros\n",
      "S775.mps.gz rate: 1.0776916896765079\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S776.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199794 rows, 121546 columns, 737604 nonzeros\n",
      "S776.mps.gz rate: 0.9683576588287562\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S777.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199673 rows, 125092 columns, 750475 nonzeros\n",
      "S777.mps.gz rate: 0.932913375755444\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S778.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199678 rows, 113533 columns, 674339 nonzeros\n",
      "S778.mps.gz rate: 1.0182061603234303\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S779.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199940 rows, 116697 columns, 716131 nonzeros\n",
      "S779.mps.gz rate: 1.0085949081810157\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S780.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199874 rows, 133731 columns, 815089 nonzeros\n",
      "S780.mps.gz rate: 0.886854955096425\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S781.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199635 rows, 101353 columns, 599222 nonzeros\n",
      "S781.mps.gz rate: 1.132674908488155\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S782.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199838 rows, 118092 columns, 721274 nonzeros\n",
      "S782.mps.gz rate: 0.984825390373607\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S783.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199807 rows, 130651 columns, 791894 nonzeros\n",
      "S783.mps.gz rate: 0.9069965021316332\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S784.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199743 rows, 120089 columns, 718052 nonzeros\n",
      "S784.mps.gz rate: 0.9734446951844049\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S785.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199895 rows, 129784 columns, 782458 nonzeros\n",
      "S785.mps.gz rate: 0.9007273623867348\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S786.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199908 rows, 129047 columns, 782563 nonzeros\n",
      "S786.mps.gz rate: 0.8950227436515378\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S787.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199874 rows, 123272 columns, 746594 nonzeros\n",
      "S787.mps.gz rate: 0.9564215718086833\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S788.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199871 rows, 118759 columns, 719852 nonzeros\n",
      "S788.mps.gz rate: 0.9733999107436069\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S789.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199888 rows, 123505 columns, 752467 nonzeros\n",
      "S789.mps.gz rate: 0.95380753815635\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S790.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199842 rows, 132577 columns, 797842 nonzeros\n",
      "S790.mps.gz rate: 0.8855231299546679\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S791.mps.gz\n",
      "Reading time = 0.35 seconds\n",
      "(null): 199873 rows, 128656 columns, 775670 nonzeros\n",
      "S791.mps.gz rate: 0.9086245491854247\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S792.mps.gz\n",
      "Reading time = 0.29 seconds\n",
      "(null): 199664 rows, 110619 columns, 654978 nonzeros\n",
      "S792.mps.gz rate: 1.0540684692503097\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S793.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199759 rows, 123016 columns, 739480 nonzeros\n",
      "S793.mps.gz rate: 0.9454054757104767\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S794.mps.gz\n",
      "Reading time = 0.34 seconds\n",
      "(null): 199925 rows, 137287 columns, 835815 nonzeros\n",
      "S794.mps.gz rate: 0.8551428758731707\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S795.mps.gz\n",
      "Reading time = 0.30 seconds\n",
      "(null): 199714 rows, 124086 columns, 741705 nonzeros\n",
      "S795.mps.gz rate: 0.9469239076124623\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S796.mps.gz\n",
      "Reading time = 0.31 seconds\n",
      "(null): 199821 rows, 122343 columns, 736183 nonzeros\n",
      "S796.mps.gz rate: 0.9506060828980817\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S797.mps.gz\n",
      "Reading time = 0.33 seconds\n",
      "(null): 199606 rows, 130925 columns, 777732 nonzeros\n",
      "S797.mps.gz rate: 0.8997517662784036\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S798.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199831 rows, 131288 columns, 782270 nonzeros\n",
      "S798.mps.gz rate: 0.8957406617512644\n",
      "Read MPS format model from file /mnt/disk1/thlee/MILP/pas/instance/CJ/new/train/S799.mps.gz\n",
      "Reading time = 0.32 seconds\n",
      "(null): 199747 rows, 123896 columns, 742086 nonzeros\n",
      "S799.mps.gz rate: 0.9435332859817912\n"
     ]
    }
   ],
   "source": [
    "rate_list, max_list, min_list, mean_list, std_list = [], [], [], [], []\n",
    "for ins_name in ins_names:\n",
    "    ins_path = f\"{ins_dir}/{ins_name}\"\n",
    "    m = gp.read(ins_path)\n",
    "\n",
    "    c_matrix = m.getA()\n",
    "    sense = np.array(m.getAttr(\"Sense\", m.getConstrs()))\n",
    "    rhs = np.array(m.getAttr(\"RHS\", m.getConstrs()))\n",
    "\n",
    "    index_ge = np.where(sense == \">\")[0]\n",
    "    c_matrix[index_ge] *= -1\n",
    "    rhs[index_ge] *= -1\n",
    "\n",
    "    rate_ = (c_matrix.sum(axis=0) == 0).sum() / c_matrix.shape[1]\n",
    "\n",
    "    rate_list.append(rate_ * 100)\n",
    "    max_list.append(c_matrix.max())\n",
    "    min_list.append(c_matrix.min())\n",
    "\n",
    "    mean_list.append(c_matrix[(c_matrix != 0)].mean())\n",
    "    std_list.append(c_matrix[(c_matrix != 0)].std())\n",
    "    print(f\"{ins_name} rate: {rate_ * 100}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.90499640654145\n",
      "7000.0\n",
      "-1500000.0\n",
      "-112.49671139797978\n",
      "4179.621046868429\n",
      "good\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(rate_list))\n",
    "print(np.mean(max_list))\n",
    "print(np.mean(min_list))\n",
    "print(np.mean(mean_list))\n",
    "print(np.mean(std_list))\n",
    "print(\"good\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Get the non-zero values from c_matrix\n",
    "non_zero_values = np.array(c_matrix[(c_matrix != 0)]).flatten()\n",
    "\n",
    "# Create the histogram\n",
    "plt.hist(non_zero_values, bins=40)\n",
    "\n",
    "# Set the labels and title\n",
    "plt.xlabel(\"Value\")\n",
    "plt.yscale(\"log\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.title(\"Histogram of Non-Zero Values in c_matrix\")\n",
    "\n",
    "# Show the histogram\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pas",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}