diff --git a/Manifest.toml b/Manifest.toml
index faa6983..f38b518 100644
--- a/Manifest.toml
+++ b/Manifest.toml
@@ -2,7 +2,7 @@
julia_version = "1.10.3"
manifest_format = "2.0"
-project_hash = "29a6145c02c22a98034a3568ff449383e5e62744"
+project_hash = "aa033784bda443e249e3bfcba6e156ffd538383e"
[[deps.ArgTools]]
uuid = "0dad84c5-d112-42e6-8d28-ef12dabb789f"
@@ -88,6 +88,12 @@ git-tree-sha1 = "8cfa272e8bdedfa88b6aefbbca7c19f1befac519"
uuid = "f0e56b4a-5159-44fe-b623-3e5288b988bb"
version = "2.3.0"
+[[deps.Conda]]
+deps = ["Downloads", "JSON", "VersionParsing"]
+git-tree-sha1 = "51cab8e982c5b598eea9c8ceaced4b58d9dd37c9"
+uuid = "8f4d0f93-b110-5947-807f-2305c1781a2d"
+version = "1.10.0"
+
[[deps.Contour]]
git-tree-sha1 = "d05d9e7b7aedff4e5b51a029dced05cfb6125781"
uuid = "d38c429a-6771-53c6-b99e-75d170b6e991"
@@ -241,6 +247,12 @@ git-tree-sha1 = "129acf094d168394e80ee1dc4bc06ec835e510a3"
uuid = "2e76f6c2-a576-52d4-95c1-20adfe4de566"
version = "2.8.1+1"
+[[deps.IJulia]]
+deps = ["Base64", "Conda", "Dates", "InteractiveUtils", "JSON", "Libdl", "Logging", "Markdown", "MbedTLS", "Pkg", "Printf", "REPL", "Random", "SoftGlobalScope", "Test", "UUIDs", "ZMQ"]
+git-tree-sha1 = "47ac8cc196b81001a711f4b2c12c97372338f00c"
+uuid = "7073ff75-c697-5162-941a-fcdaad2a7d2a"
+version = "1.24.2"
+
[[deps.InteractiveUtils]]
deps = ["Markdown"]
uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
@@ -654,6 +666,12 @@ version = "1.1.0"
[[deps.Sockets]]
uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
+[[deps.SoftGlobalScope]]
+deps = ["REPL"]
+git-tree-sha1 = "986ec2b6162ccb95de5892ed17832f95badf770c"
+uuid = "b85f4697-e234-5449-a836-ec8e2f98b302"
+version = "1.1.0"
+
[[deps.SortingAlgorithms]]
deps = ["DataStructures"]
git-tree-sha1 = "66e0a8e672a0bdfca2c3f5937efb8538b9ddc085"
@@ -759,6 +777,11 @@ git-tree-sha1 = "ca0969166a028236229f63514992fc073799bb78"
uuid = "41fe7b60-77ed-43a1-b4f0-825fd5a5650d"
version = "0.2.0"
+[[deps.VersionParsing]]
+git-tree-sha1 = "58d6e80b4ee071f5efd07fda82cb9fbe17200868"
+uuid = "81def892-9a0e-5fdd-b105-ffc91e053289"
+version = "1.3.0"
+
[[deps.Vulkan_Loader_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Wayland_jll", "Xorg_libX11_jll", "Xorg_libXrandr_jll", "xkbcommon_jll"]
git-tree-sha1 = "2f0486047a07670caad3a81a075d2e518acc5c59"
@@ -939,6 +962,18 @@ git-tree-sha1 = "e92a1a012a10506618f10b7047e478403a046c77"
uuid = "c5fb5394-a638-5e4d-96e5-b29de1b5cf10"
version = "1.5.0+0"
+[[deps.ZMQ]]
+deps = ["FileWatching", "Sockets", "ZeroMQ_jll"]
+git-tree-sha1 = "356d2bdcc0bce90aabee1d1c0f6d6f301eda8f77"
+uuid = "c2297ded-f4af-51ae-bb23-16f91089e4e1"
+version = "1.2.2"
+
+[[deps.ZeroMQ_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "libsodium_jll"]
+git-tree-sha1 = "42f97fb27394378591666ab0e9cee369e6d0e1f9"
+uuid = "8f1865be-045e-5c20-9c9f-bfbfb0764568"
+version = "4.3.5+0"
+
[[deps.Zlib_jll]]
deps = ["Libdl"]
uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
@@ -1009,6 +1044,12 @@ git-tree-sha1 = "93284c28274d9e75218a416c65ec49d0e0fcdf3d"
uuid = "b53b4c65-9356-5827-b1ea-8c7a1a84506f"
version = "1.6.40+0"
+[[deps.libsodium_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "848ab3d00fe39d6fbc2a8641048f8f272af1c51e"
+uuid = "a9144af2-ca23-56d9-984f-0d03f7b5ccf8"
+version = "1.0.20+0"
+
[[deps.libvorbis_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Ogg_jll", "Pkg"]
git-tree-sha1 = "b910cb81ef3fe6e78bf6acee440bda86fd6ae00c"
diff --git a/Project.toml b/Project.toml
index 8a4a545..50869f4 100644
--- a/Project.toml
+++ b/Project.toml
@@ -5,6 +5,7 @@ version = "0.2.0"
[deps]
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
+IJulia = "7073ff75-c697-5162-941a-fcdaad2a7d2a"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
diff --git a/notebooks/Dealing with constrained problems.ipynb b/notebooks/Dealing with constrained problems.ipynb
index 40f7d39..ec5ea8d 100644
--- a/notebooks/Dealing with constrained problems.ipynb
+++ b/notebooks/Dealing with constrained problems.ipynb
@@ -88,24 +88,18 @@
}
],
"source": [
- "include(\"../src/bounds.jl\")\n",
- "include(\"../src/solution.jl\")\n",
- "include(\"../src/operator.jl\")\n",
- "include(\"../src/algorithm.jl\")\n",
- "include(\"../src/component.jl\")\n",
- "include(\"../src/utils.jl\")\n",
- "include(\"../src/constrainedProblem.jl\")\n",
+ "using metajul\n",
"\n",
- "problem = srinivasProblem()\n",
+ "problem = srinivas()\n",
"\n",
"solver::NSGAII = NSGAII()\n",
"solver.problem = problem\n",
"solver.populationSize = 100\n",
"\n",
- "solver.termination = TerminationByEvaluations((numberOfEvaluationsToStop = 25000, ))\n",
+ "solver.termination = TerminationByEvaluations(25000)\n",
"\n",
- "solver.mutation = PolynomialMutation((probability=1.0/numberOfVariables(problem), distributionIndex=20.0, bounds=problem.bounds))\n",
- "solver.crossover = SBXCrossover((probability=1.0, distributionIndex=20.0, bounds=problem.bounds))\n",
+ "solver.mutation = PolynomialMutation(1.0/numberOfVariables(problem), 20.0, problem.bounds)\n",
+ "solver.crossover = SBXCrossover(1.0, 20.0, problem.bounds)\n",
"\n",
"solver.dominanceComparator = compareForConstraintsAndDominance"
]
@@ -139,198 +133,296 @@
"outputs": [
{
"data": {
+ "image/png": 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+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/html": [
+ "\n",
+ "\n"
]
},
"execution_count": 3,
@@ -363,15 +455,15 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Julia 1.8.0",
+ "display_name": "Julia 1.10.3",
"language": "julia",
- "name": "julia-1.8"
+ "name": "julia-1.10"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
- "version": "1.8.0"
+ "version": "1.10.3"
}
},
"nbformat": 4,
diff --git a/notebooks/Defining problems.ipynb b/notebooks/Defining problems.ipynb
index 0ea1c68..dbd2ad3 100644
--- a/notebooks/Defining problems.ipynb
+++ b/notebooks/Defining problems.ipynb
@@ -81,7 +81,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 6,
"id": "44759988",
"metadata": {},
"outputs": [
@@ -89,7 +89,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "ContinuousProblem{Real}(Bounds{Real}[Bounds{Real}(-1000.0, 1000.0)], Function[var\"#9#10\"(), var\"#11#12\"()], Function[], \"Schaffer\")\n"
+ "ContinuousProblem{Real}(Bounds{Real}[Bounds{Real}(-1000.0, 1000.0)], Function[var\"#13#14\"(), var\"#15#16\"()], Function[], \"Schaffer\")\n"
]
}
],
@@ -165,7 +165,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 5,
"id": "d496dfdc",
"metadata": {},
"outputs": [
@@ -176,7 +176,7 @@
"Number of variables: 1\n",
"Number of objectives: 2\n",
"Number of constraints: 0\n",
- "Name: Schaffer\n",
+ "Name: Schaffer2\n",
"Bounds: Bounds{Real}[Bounds{Real}(-1000.0, 1000.0)]\n"
]
}
@@ -254,7 +254,7 @@
"This problem can be implemented as follows. First, we create a struct called ``ZDT6`` to contain the problem bounds:\n",
" \n",
"```julia\n",
- "struct ZDT6 <: AbstractContinuousProblem{Float64}\n",
+ "struct ProblemZDT6 <: AbstractContinuousProblem{Float64}\n",
" bounds::Vector{Bounds{Float64}}\n",
"end\n",
"```"
@@ -268,25 +268,29 @@
"Next we define a function called ``zdt6Problem()`` which initializes the problem bounds and the set of functions to retrieve the problem data:\n",
"\n",
"```julia\n",
- "function zdt6Problem(numberOfVariables::Int=10)\n",
+ "function ZDT6(numberOfVariables::Int=10)\n",
" bounds = [Bounds{Float64}(0.0, 1.0) for _ in range(1, numberOfVariables)]\n",
"\n",
- " return ZDT6(bounds)\n",
+ " return ProblemZDT6(bounds)\n",
"end\n",
"\n",
- "function numberOfVariables(problem::ZDT6)\n",
+ "function numberOfVariables(problem::ProblemZDT6)\n",
" return length(problem.bounds)\n",
"end\n",
"\n",
- "function numberOfObjectives(problem::ZDT6)\n",
+ "function numberOfObjectives(problem::ProblemZDT6)\n",
" return 2\n",
"end\n",
"\n",
- "function numberOfConstraints(problem::ZDT6)\n",
+ "function numberOfConstraints(problem::ProblemZDT6)\n",
" return 0\n",
"end\n",
"\n",
- "function name(problem::ZDT6)\n",
+ "function bounds(problem::ProblemZDT6)\n",
+ " return problem.bounds\n",
+ "end\n",
+ "\n",
+ "function name(problem::ProblemZDT6)\n",
" return \"ZDT6\"\n",
"end\n",
"\n",
@@ -300,7 +304,7 @@
"source": [
"The last step is to implement the ``evaluate`` method containing the code of the objective functions:\n",
"```julia\n",
- "function evaluate(solution::ContinuousSolution{Float64}, problem::ZDT6)::ContinuousSolution{Float64}\n",
+ "function evaluate(solution::ContinuousSolution{Float64}, problem::ProblemZDT6)::ContinuousSolution{Float64}\n",
" x = solution.variables\n",
" @assert length(x) == numberOfVariables(problem) \"The number of variables of the solution to be evaluated is not correct\"\n",
"\n",
@@ -333,30 +337,32 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "00ca6da7",
"metadata": {},
"outputs": [],
"source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "f83004f7",
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "language": "python",
- "name": "python3"
+ "display_name": "Julia 1.10.3",
+ "language": "julia",
+ "name": "julia-1.10"
},
"language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.11.5"
+ "file_extension": ".jl",
+ "mimetype": "application/julia",
+ "name": "julia",
+ "version": "1.10.3"
}
},
"nbformat": 4,
diff --git a/notebooks/NSGA-II notebook.ipynb b/notebooks/NSGA-II notebook.ipynb
index ccbf2f0..bb51e3b 100644
--- a/notebooks/NSGA-II notebook.ipynb
+++ b/notebooks/NSGA-II notebook.ipynb
@@ -12,20 +12,12 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 31,
"id": "ebc4e903",
"metadata": {},
"outputs": [],
"source": [
- "include(\"../src/bounds.jl\")\n",
- "include(\"../src/solution.jl\")\n",
- "include(\"../src/operator.jl\")\n",
- "include(\"../src/continuousProblem.jl\")\n",
- "include(\"../src/binaryProblem.jl\")\n",
- "include(\"../src/algorithm.jl\")\n",
- "include(\"../src/component.jl\")\n",
- "include(\"../src/utils.jl\")\n",
- "\n",
+ "using metajul\n",
"using Dates"
]
},
@@ -47,25 +39,23 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 32,
"id": "f45c2dcd",
"metadata": {},
"outputs": [
{
- "ename": "UndefVarError",
- "evalue": "UndefVarError: `kursaweProblem` not defined",
- "output_type": "error",
- "traceback": [
- "UndefVarError: `kursaweProblem` not defined\n",
- "\n",
- "Stacktrace:\n",
- " [1] top-level scope\n",
- " @ ~/Softw/julia/metajul/notebooks/NSGA-II notebook.ipynb:1"
- ]
+ "data": {
+ "text/plain": [
+ "ContinuousProblem{Float64}(Bounds{Float64}[Bounds{Float64}(-5.0, 5.0), Bounds{Float64}(-5.0, 5.0), Bounds{Float64}(-5.0, 5.0)], Function[metajul.var\"#147#149\"{Int64}(3), metajul.var\"#148#150\"{Int64}(3)], Function[], \"Kursawe\")"
+ ]
+ },
+ "execution_count": 32,
+ "metadata": {},
+ "output_type": "execute_result"
}
],
"source": [
- "problem = kursaweProblem()"
+ "problem = kursawe()"
]
},
{
@@ -78,7 +68,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 21,
"id": "bef9eff3",
"metadata": {},
"outputs": [
@@ -88,8 +78,9 @@
"100"
]
},
+ "execution_count": 21,
"metadata": {},
- "output_type": "display_data"
+ "output_type": "execute_result"
}
],
"source": [
@@ -100,29 +91,25 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 22,
"id": "a9b91d3b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "\"# Alternative crossover operator\\nsolver.crossover = BLXAlphaCrossover((probability=1.0, alpha=0.5, bounds=problem.bounds))\\n\""
+ "SBXCrossover(1.0, 20.0, Bounds{Float64}[Bounds{Float64}(-5.0, 5.0), Bounds{Float64}(-5.0, 5.0), Bounds{Float64}(-5.0, 5.0)])"
]
},
+ "execution_count": 22,
"metadata": {},
- "output_type": "display_data"
+ "output_type": "execute_result"
}
],
"source": [
- "solver.termination = TerminationByEvaluations((numberOfEvaluationsToStop = 250000, ))\n",
- "solver.mutation = PolynomialMutation((probability=1.0/numberOfVariables(problem), distributionIndex=20.0, bounds=problem.bounds))\n",
- "solver.crossover = SBXCrossover((probability=1.0, distributionIndex=20.0, bounds=problem.bounds))\n",
- "\n",
- "\"\"\"\n",
- "# Alternative crossover operator\n",
- "solver.crossover = BLXAlphaCrossover((probability=1.0, alpha=0.5, bounds=problem.bounds))\n",
- "\"\"\"\n"
+ "solver.termination = TerminationByEvaluations(25000)\n",
+ "solver.mutation = PolynomialMutation(1.0/numberOfVariables(problem),20.0, problem.bounds)\n",
+ "solver.crossover = SBXCrossover(1.0, 20.0, problem.bounds)"
]
},
{
@@ -135,7 +122,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 23,
"id": "d5445a96",
"metadata": {},
"outputs": [
@@ -143,7 +130,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Computing time: 7497 milliseconds\n"
+ "Computing time: 848 milliseconds\n"
]
}
],
@@ -165,302 +152,315 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 24,
"id": "83b0fd8f",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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