feat: ajout du notebook julia d'exemple
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exemple/solution_ciment.ipynb
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exemple/solution_ciment.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Exemple de modèle et résolution du problème de Fabrication du ciment"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
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"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Project.toml`\n",
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"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Manifest.toml`\n",
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"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
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"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Project.toml`\n",
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"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Manifest.toml`\n"
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]
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}
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],
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"source": [
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"#importer les packages utiles\n",
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"import Pkg; Pkg.add(\"Cbc\")\n",
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"Pkg.add(\"JuMP\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"ename": "LoadError",
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"evalue": "\u001b[91mMethodError: no method matching Model(::Type{Cbc.Optimizer})\u001b[39m\n\u001b[91m\u001b[0mClosest candidates are:\u001b[39m\n\u001b[91m\u001b[0m Model(::Any, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m) at /Users/sungueve/.julia/packages/JuMP/MsUSY/src/JuMP.jl:126\u001b[39m\n\u001b[91m\u001b[0m Model(; caching_mode, solver) at /Users/sungueve/.julia/packages/JuMP/MsUSY/src/JuMP.jl:161\u001b[39m\n\u001b[91m\u001b[0m Model(\u001b[91m::MathOptInterface.AbstractOptimizer\u001b[39m, \u001b[91m::Dict{MathOptInterface.ConstraintIndex,AbstractShape}\u001b[39m, \u001b[91m::Set{Any}\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Dict{Symbol,Any}\u001b[39m, \u001b[91m::Int64\u001b[39m, \u001b[91m::Dict{Symbol,Any}\u001b[39m) at /Users/sungueve/.julia/packages/JuMP/MsUSY/src/JuMP.jl:126\u001b[39m\n\u001b[91m\u001b[0m ...\u001b[39m",
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"output_type": "error",
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"traceback": [
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"\u001b[91mMethodError: no method matching Model(::Type{Cbc.Optimizer})\u001b[39m\n\u001b[91m\u001b[0mClosest candidates are:\u001b[39m\n\u001b[91m\u001b[0m Model(::Any, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m) at /Users/sungueve/.julia/packages/JuMP/MsUSY/src/JuMP.jl:126\u001b[39m\n\u001b[91m\u001b[0m Model(; caching_mode, solver) at /Users/sungueve/.julia/packages/JuMP/MsUSY/src/JuMP.jl:161\u001b[39m\n\u001b[91m\u001b[0m Model(\u001b[91m::MathOptInterface.AbstractOptimizer\u001b[39m, \u001b[91m::Dict{MathOptInterface.ConstraintIndex,AbstractShape}\u001b[39m, \u001b[91m::Set{Any}\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Any\u001b[39m, \u001b[91m::Dict{Symbol,Any}\u001b[39m, \u001b[91m::Int64\u001b[39m, \u001b[91m::Dict{Symbol,Any}\u001b[39m) at /Users/sungueve/.julia/packages/JuMP/MsUSY/src/JuMP.jl:126\u001b[39m\n\u001b[91m\u001b[0m ...\u001b[39m",
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"",
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"Stacktrace:",
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" [1] top-level scope at In[3]:11",
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" [2] include_string(::Function, ::Module, ::String, ::String) at ./loading.jl:1091"
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]
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}
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],
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"source": [
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"using Cbc\n",
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"using JuMP\n",
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"\n",
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"# data\n",
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"N = 2 # nombre de ciments disponibles\n",
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"c = [50,70] # prix de vente par ciment\n",
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"b = [360,480] # temps de disponibilité du four et de l'atelier\n",
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"A = [40 12;20 30] # temps nécessaire de calcination (four) et de broyage (atelier) par ciment\n",
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"\n",
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"# set optimizer\n",
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"model = Model(Cbc.Optimizer)\n",
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"\n",
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"# define variables\n",
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"@variable(model, ciment[1:N] >= 0)\n",
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"\n",
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"# define objective function\n",
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"@objective(model, Max, sum(c[i]*ciment[i] for i in 1:N))\n",
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"\n",
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"# define constraints\n",
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"for i in 1:length(b)\n",
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" @constraint(model, sum(A[i,j]*ciment[j] for j in 1:N) <= b[i])\n",
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"end\n",
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"\n",
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"println(model)\n",
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"\n",
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"# run optimization\n",
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"optimize!(model)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Solution obtenue:\n",
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"\t benefice = 1137.5\n",
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"\t quantite de ciment 1 = 5.249999999999999\n",
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"\t quantite de ciment 2 = 12.5\n"
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]
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}
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],
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"source": [
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"# print solution\n",
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"println(\"Solution obtenue:\")\n",
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"println(\"\\t benefice = $(objective_value(model))\")\n",
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"for i in 1:N\n",
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" println(\"\\t quantite de ciment $i = $(value(ciment[i]))\")\n",
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"end\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Julia 1.5.3",
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"language": "julia",
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"name": "julia-1.5"
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},
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"language_info": {
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"file_extension": ".jl",
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"mimetype": "application/julia",
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"name": "julia",
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"version": "1.5.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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