ga-dev.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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     "slide_type": ""
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   "source": [
    "from dataclasses import dataclass\n",
    "from pandas import DataFrame\n",
    "import pygad\n",
    "import numpy\n",
    "import pandas as pd\n",
    "from typing import Callable, Dict, Any, List, Optional\n",
    "from icecream import ic\n",
    "\n",
    "from order_optimization.container import ModelInterface\n",
    "\n",
    "from ordplan_project.settings import MIN_TRIM,PENALTY_VALUE, ROLL_PAPER\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class GA():\n",
    "    orders: DataFrame\n",
    "    size: float = 66\n",
    "    num_generations: int = 50\n",
    "    out_range: int = 6\n",
    "    showOutput: bool = False\n",
    "    save_solutions: bool = False\n",
    "    showZero: bool = False\n",
    "    selector: Dict[str, Any] | None = None\n",
    "    set_progress: Callable | None = None\n",
    "    current_generation: int = 0\n",
    "    _penalty:int = 0 \n",
    "    _penalty_value:int = PENALTY_VALUE\n",
    "    blade:Optional[int] = None\n",
    "    \n",
    "    def __post_init__(self):\n",
    "        if self.orders is None:\n",
    "            raise ValueError(\"Orders is empty!\")\n",
    "        self.orders = self.orders[self.orders['quantity'] > 0].reset_index(drop=True)\n",
    "        self._paper_size  = self.size\n",
    "\n",
    "        self.model = pygad.GA(\n",
    "            num_generations=self.num_generations,\n",
    "            num_parents_mating=60,\n",
    "            fitness_func=self.fitness_function,\n",
    "            sol_per_pop=120,\n",
    "            num_genes=len(self.orders),\n",
    "            parent_selection_type=\"tournament\",\n",
    "            gene_type=int,\n",
    "            init_range_low=0,\n",
    "            init_range_high=self.out_range,\n",
    "            crossover_type=\"uniform\",\n",
    "            mutation_type=\"random\",\n",
    "            mutation_percent_genes=10,\n",
    "            on_generation=self.on_gen,\n",
    "            save_solutions=self.save_solutions,\n",
    "        )\n",
    "\n",
    "        \n",
    "    def paper_type_logic(self, solution):\n",
    "        init_type = None\n",
    "        orders = self.orders\n",
    "        match orders[\"edge_type\"][self.get_first_solution(solution)]:\n",
    "            case \"X\":\n",
    "                init_type = 1\n",
    "            case \"N\":\n",
    "                init_type = 2\n",
    "            case \"W\":\n",
    "                init_type = 2\n",
    "\n",
    "        if init_type is not None:\n",
    "            for index, out in enumerate(solution):\n",
    "                if out >= 1:\n",
    "                    match init_type:\n",
    "                        case 1:\n",
    "                            if orders[\"edge_type\"][index] not in [\n",
    "                                \"X\",\n",
    "                                \"Y\",\n",
    "                            ]:  # Changed OR to AND condition\n",
    "                                self._penalty += self._penalty_value\n",
    "                        case 2:\n",
    "                            if orders[\"edge_type\"][index] == \"X\":\n",
    "                                self._penalty += self._penalty_value\n",
    "\n",
    "    def least_order_logic(self, solution):\n",
    "        init_order = None\n",
    "        orders = self.orders\n",
    "\n",
    "        init_order = orders[\"quantity\"][self.get_first_solution(solution)]\n",
    "\n",
    "        for index, out in enumerate(solution):\n",
    "            if out >= 1 and orders[\"quantity\"][index] < init_order:\n",
    "                self._penalty += self._penalty_value\n",
    "\n",
    "    @staticmethod\n",
    "    def get_first_solution(solution) -> int:\n",
    "        for index, out in enumerate(solution):\n",
    "            if out >= 1:\n",
    "                return index\n",
    "        return 0\n",
    "\n",
    "    def paper_out_logic(self, solution):\n",
    "        if sum(solution) > 5:\n",
    "            if sum(solution) <= 6:\n",
    "                init = 0\n",
    "                for index, out in enumerate(solution):\n",
    "                    if out>=1:\n",
    "                        if self.orders['edge_type'][index]=='X' and init==0:\n",
    "                            init = 1\n",
    "                            continue\n",
    "                        if self.orders['edge_type'][index]=='Y' and init==1:\n",
    "                            return                \n",
    "            \n",
    "            self._penalty += self._penalty_value * sum(solution)  # ยิ่งเกิน ยิ่ง _penaltyเยอะ\n",
    "        \n",
    "        \n",
    "        order_length = 0\n",
    "        for index, out in enumerate(solution):\n",
    "            if out >= 1:\n",
    "                order_length += 1\n",
    "        if order_length > 2:\n",
    "            self._penalty += self._penalty_value * order_length  # ยิ่งเกิน ยิ่ง _penaltyเยอะ\n",
    "\n",
    "    def paper_size_logic(self, _output):\n",
    "        if _output > self._paper_size :  # ถ้าผลรวมมีค่ามากกว่า roll กำหนดขึ้น _penalty\n",
    "            self._penalty += self._penalty_value * (\n",
    "                _output - self._paper_size \n",
    "            )  # ยิ่งเกิน ยิ่ง _penaltyเยอะ\n",
    "\n",
    "    def paper_trim_logic(self, _fitness_values):\n",
    "        if abs(_fitness_values) <= MIN_TRIM:  # ถ้าผลรวมมีค่าน้อยกว่า _penalty > เงื่อนไขบริษัท\n",
    "            self._penalty += self._penalty_value\n",
    "\n",
    "    def selector_logic(self, solution: List[int])->List[int]:\n",
    "        if self.selector is None:\n",
    "            return solution\n",
    "        \n",
    "        try:\n",
    "            solution[0] = self.selector[\"out\"] #lock the first to be out (the first order is also the selector, manage by ORD)\n",
    "        except KeyError:\n",
    "            pass\n",
    "\n",
    "        if solution[0] == 0: \n",
    "            solution[0] += 1\n",
    "\n",
    "        return solution\n",
    "\n",
    "    def fitness_function(self, ga_instance, solution, solution_idx):\n",
    "        self._penalty = 0\n",
    "\n",
    "        solution = self.selector_logic(solution)\n",
    "\n",
    "        self.paper_type_logic(solution)\n",
    "\n",
    "        self.least_order_logic(solution)\n",
    "\n",
    "        self.paper_out_logic(solution)\n",
    "\n",
    "        _output = numpy.sum(solution * self.orders[\"width\"])  # ผลรวมของตัดกว้างทั้งหมด\n",
    "        self.paper_size_logic(_output)\n",
    "\n",
    "        _fitness_values = -self._paper_size  + _output  # ผลต่างของกระดาษที่มีกับออเดอร์ ยิ่งเยอะยิ่งดี\n",
    "        self.paper_trim_logic(_fitness_values)\n",
    "        return _fitness_values - self._penalty  # ลบด้วย _penalty\n",
    "\n",
    "    def on_gen(self, ga_instance):\n",
    "\n",
    "        self.current_generation += 1\n",
    "        if self.set_progress:\n",
    "            progress = (self.current_generation / self.num_generations) * 100\n",
    "            self.set_progress(progress)\n",
    "\n",
    "        orders = self.orders\n",
    "\n",
    "        solution = ga_instance.best_solution()[0]\n",
    "\n",
    "        _output = pd.DataFrame(\n",
    "            {   \n",
    "                \"id\": orders['id'].unique(),\n",
    "                \"blade\": 0,\n",
    "                \"order_number\": orders[\"order_number\"],\n",
    "                \"num_orders\": orders[\"quantity\"],\n",
    "                \"component_type\": orders[\"component_type\"],\n",
    "                \"cut_width\": orders[\"width\"],\n",
    "                \"cut_len\": orders[\"length\"],\n",
    "                \"type\": orders[\"edge_type\"],\n",
    "                \"deadline\": orders[\"due_date\"],\n",
    "                \"out\": solution,\n",
    "            }\n",
    "        )\n",
    "\n",
    "        if not self.showZero:\n",
    "            _output = _output[_output[\"out\"] >= 1]\n",
    "        _output = _output.reset_index(drop=True)\n",
    "\n",
    "\n",
    "        _output = self.blade_logic(_output)\n",
    "\n",
    "        self._fitness_values = ga_instance.best_solution()[1]\n",
    "        self._output = _output\n",
    "\n",
    "        if self.showOutput:\n",
    "            self.show(ga_instance, _output)\n",
    "\n",
    "    def blade_logic(self, output: DataFrame) -> DataFrame:\n",
    "        blade_list: List[Dict[str,int]] = []\n",
    "        for idx in output.index:\n",
    "            blade_val = idx+1\n",
    "            if self.blade is not None:\n",
    "                blade_val = self.blade\n",
    "            blade_list.append({\"blade\": blade_val})\n",
    "\n",
    "        blade_df = pd.DataFrame(blade_list)\n",
    "        output = pd.concat([output, blade_df], axis=1)\n",
    "        return output\n",
    "\n",
    "    def show(self, ga_instance, _output):\n",
    "        _paper_size  = self._paper_size \n",
    "        print(\"Generation : \", ga_instance.generations_completed)\n",
    "        print(\"Solution :\")\n",
    "\n",
    "        with pd.option_context(\n",
    "            \"display.max_columns\",\n",
    "            None,\n",
    "            \"display.width\",\n",
    "            None,\n",
    "            \"display.colheader_justify\",\n",
    "            \"left\",\n",
    "        ):\n",
    "            print(_output.to_string(index=False))\n",
    "\n",
    "        print(\"Roll :\", _paper_size )\n",
    "        print(\"Used :\", _paper_size  + self._fitness_values)\n",
    "        print(\"Trim :\", abs(self._fitness_values))\n",
    "        print(\"\\n\")\n",
    "\n",
    "    @property\n",
    "    def run(self) -> Callable:\n",
    "        return self.model.run\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data = pd.DataFrame(\n",
    "        {\n",
    "            \"order_number\": [1, 2, 3, 4, 5],\n",
    "            \"quantity\": [100, 200, 1500, 500, 250],\n",
    "            \"component_type\": [\"A\", \"B\", \"C\", \"D\", \"E\"],\n",
    "            \"width\": [66.04, 66.04, 66.04, 66.04, 80],\n",
    "            \"length\": [200.0, 200.0, 200.0, 200.0, 200.0],\n",
    "            \"edge_type\": [\"X\", \"N\", \"W\", \"X\", \"Y\"],\n",
    "            \"due_date\": [\"08/01/23\", \"08/01/23\", \"08/05/23\", \"08/10/23\", \"08/15/23\"],\n",
    "            \"front_sheet\": [\"P1\", \"P2\", \"P3\", \"P4\", \"P5\"],\n",
    "            \"c_wave\": [\"C1\", \"C2\", \"C3\", \"C4\", \"C5\"],\n",
    "            \"middle_sheet\": [\"M1\", \"M2\", \"M3\", \"M4\", \"M5\"],\n",
    "            \"b_wave\": [\"B1\", \"B2\", \"B3\", \"B4\", \"B5\"],\n",
    "            \"back_sheet\": [\"B1\", \"B2\", \"B3\", \"B4\", \"B5\"],\n",
    "            \"level\": [1, 2, 3, 1, 2],\n",
    "            \"left_edge_cut\": [0, 1, 0, 1, 0],\n",
    "            \"middle_edge_cut\": [1, 0, 1, 0, 1],\n",
    "            \"right_edge_cut\": [0, 1, 0, 1, 0],\n",
    "            \"id\": [1,2,3,4,5]\n",
    "        }\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vorkna/Desktop/paper_cutting_project/.venv/lib/python3.12/site-packages/pygad/pygad.py:748: UserWarning: The percentage of genes to mutate (mutation_percent_genes=10) resulted in selecting (0) genes. The number of genes to mutate is set to 1 (mutation_num_genes=1).\n",
      "If you do not want to mutate any gene, please set mutation_type=None.\n",
      "  warnings.warn(f\"The percentage of genes to mutate (mutation_percent_genes={mutation_percent_genes}) resulted in selecting ({mutation_num_genes}) genes. The number of genes to mutate is set to 1 (mutation_num_genes=1).\\nIf you do not want to mutate any gene, please set mutation_type=None.\")\n",
      "/home/vorkna/Desktop/paper_cutting_project/.venv/lib/python3.12/site-packages/pygad/pygad.py:1139: UserWarning: The 'delay_after_gen' parameter is deprecated starting from PyGAD 3.3.0. To delay or pause the evolution after each generation, assign a callback function/method to the 'on_generation' parameter to adds some time delay.\n",
      "  warnings.warn(\"The 'delay_after_gen' parameter is deprecated starting from PyGAD 3.3.0. To delay or pause the evolution after each generation, assign a callback function/method to the 'on_generation' parameter to adds some time delay.\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation :  1\n",
      "Solution :\n",
      " id  blade  order_number  num_orders component_type  cut_width  cut_len type deadline  out  blade\n",
      "4   0      4             500         D              66.04      200.0    X    08/10/23 2    1     \n",
      "Roll : 66\n",
      "Used : -65947.92000000001\n",
      "Trim : 66013.92000000001\n",
      "\n",
      "\n",
      "Generation :  2\n",
      "Solution :\n",
      " id  blade  order_number  num_orders component_type  cut_width  cut_len type deadline  out  blade\n",
      "2   0      2             200         B              66.04      200.0    N    08/01/23 1    1     \n",
      "Roll : 66\n",
      "Used : -973.9600000000064\n",
      "Trim : 1039.9600000000064\n",
      "\n",
      "\n",
      "Generation :  3\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  4\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  5\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  6\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  7\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  8\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  9\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  10\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  11\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  12\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  13\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  14\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  15\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  16\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  17\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  18\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  19\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  20\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  21\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  22\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  23\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  24\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  25\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  26\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  27\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  28\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  29\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  30\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  31\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  32\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  33\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  34\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  35\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  36\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  37\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  38\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  39\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  40\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  41\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  42\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  43\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  44\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  45\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  46\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  47\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  48\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  49\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n",
      "Generation :  50\n",
      "Solution :\n",
      "Empty DataFrame\n",
      "Columns: [id, blade, order_number, num_orders, component_type, cut_width, cut_len, type, deadline, out]\n",
      "Index: []\n",
      "Roll : 66\n",
      "Used : 0.0\n",
      "Trim : 66.0\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ga_instance = GA(test_data,showOutput=True)\n",
    "ga_instance.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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