feat: ajout de deux notebooks

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Laureηt 2021-11-23 22:56:53 +01:00
parent be1cfaa57e
commit 9f1515c8b8
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GPG key ID: D88C6B294FD40994
3 changed files with 403 additions and 31 deletions

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@ -9,43 +9,68 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Project.toml`\n",
"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Manifest.toml`\n",
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Project.toml`\n",
"\u001b[32m\u001b[1mNo Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.5/Manifest.toml`\n"
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Project.toml`\n",
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Manifest.toml`\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Project.toml`\n",
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Manifest.toml`\n"
]
}
],
"source": [
"#importer les packages utiles\n",
"import Pkg; Pkg.add(\"Cbc\")\n",
"import Pkg;\n",
"Pkg.add(\"Cbc\")\n",
"Pkg.add(\"JuMP\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 8,
"metadata": {},
"outputs": [
{
"ename": "LoadError",
"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",
"output_type": "error",
"traceback": [
"\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",
"",
"Stacktrace:",
" [1] top-level scope at In[3]:11",
" [2] include_string(::Function, ::Module, ::String, ::String) at ./loading.jl:1091"
"name": "stdout",
"output_type": "stream",
"text": [
"Max 50 ciment[1] + 70 ciment[2]\n",
"Subject to\n",
" 40 ciment[1] + 12 ciment[2] ≤ 360.0\n",
" 20 ciment[1] + 30 ciment[2] ≤ 480.0\n",
" ciment[1] ≥ 0.0\n",
" ciment[2] ≥ 0.0\n",
"\n",
"Presolve 2 (0) rows, 2 (0) columns and 4 (0) elements\n",
"0 Obj -0 Dual inf 120 (2)\n",
"2 Obj 1137.5\n",
"Optimal - objective value 1137.5\n",
"Optimal objective 1137.5 - 2 iterations time 0.002\n"
]
}
],
@ -76,12 +101,12 @@
"println(model)\n",
"\n",
"# run optimization\n",
"optimize!(model)\n"
"optimize!(model)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"execution_count": 9,
"metadata": {},
"outputs": [
{
@ -101,28 +126,21 @@
"println(\"\\t benefice = $(objective_value(model))\")\n",
"for i in 1:N\n",
" println(\"\\t quantite de ciment $i = $(value(ciment[i]))\")\n",
"end\n"
"end"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.5.3",
"display_name": "Julia 1.6.3",
"language": "julia",
"name": "julia-1.5"
"name": "julia-1.6"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.5.3"
"version": "1.6.3"
}
},
"nbformat": 4,

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Exemple de modèle et résolution du problème de Fabrication du voitures"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Project.toml`\n",
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Manifest.toml`\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Project.toml`\n",
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Manifest.toml`\n"
]
}
],
"source": [
"#importer les packages utiles\n",
"import Pkg;\n",
"Pkg.add(\"Cbc\")\n",
"Pkg.add(\"JuMP\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Max 10000 voitures[1] + 9000 voitures[2]\n",
"Subject to\n",
" 10 voitures[1] + 20 voitures[2] ≤ 15000.0\n",
" 6 voitures[1] + 5 voitures[2] ≤ 6000.0\n",
" voitures[1] ≤ 800.0\n",
" voitures[1] ≥ 0.0\n",
" voitures[2] ≥ 0.0\n",
" voitures[1] integer\n",
" voitures[2] integer\n",
"\n",
"Welcome to the CBC MILP Solver \n",
"Version: 2.10.5 \n",
"Build Date: Jan 1 1970 \n",
"\n",
"command line - Cbc_C_Interface -solve -quit (default strategy 1)\n",
"Continuous objective value is 1.02857e+07 - 0.00 seconds\n",
"Cgl0004I processed model has 2 rows, 2 columns (2 integer (0 of which binary)) and 4 elements\n",
"Cutoff increment increased from 1e-05 to 1000\n",
"Cbc0012I Integer solution of -10272000 found by DiveCoefficient after 0 iterations and 0 nodes (0.00 seconds)\n",
"Cbc0012I Integer solution of -10284000 found by DiveCoefficient after 3 iterations and 0 nodes (0.01 seconds)\n",
"Cbc0031I 1 added rows had average density of 2\n",
"Cbc0013I At root node, 1 cuts changed objective from -10285714 to -10284000 in 21 passes\n",
"Cbc0014I Cut generator 0 (Probing) - 0 row cuts average 0.0 elements, 47 column cuts (47 active) in 0.001 seconds - new frequency is 1\n",
"Cbc0014I Cut generator 1 (Gomory) - 4 row cuts average 2.0 elements, 0 column cuts (0 active) in 0.001 seconds - new frequency is 1\n",
"Cbc0014I Cut generator 2 (Knapsack) - 0 row cuts average 0.0 elements, 0 column cuts (0 active) in 0.000 seconds - new frequency is -100\n",
"Cbc0014I Cut generator 3 (Clique) - 0 row cuts average 0.0 elements, 0 column cuts (0 active) in 0.000 seconds - new frequency is -100\n",
"Cbc0014I Cut generator 4 (MixedIntegerRounding2) - 0 row cuts average 0.0 elements, 0 column cuts (0 active) in 0.000 seconds - new frequency is -100\n",
"Cbc0014I Cut generator 5 (FlowCover) - 0 row cuts average 0.0 elements, 0 column cuts (0 active) in 0.000 seconds - new frequency is -100\n",
"Cbc0001I Search completed - best objective -10284000, took 3 iterations and 0 nodes (0.01 seconds)\n",
"Cbc0035I Maximum depth 0, 0 variables fixed on reduced cost\n",
"Cuts at root node changed objective from -1.02857e+07 to -1.0284e+07\n",
"Probing was tried 21 times and created 47 cuts of which 0 were active after adding rounds of cuts (0.001 seconds)\n",
"Gomory was tried 21 times and created 4 cuts of which 0 were active after adding rounds of cuts (0.001 seconds)\n",
"Knapsack was tried 21 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
"Clique was tried 21 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
"MixedIntegerRounding2 was tried 21 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
"FlowCover was tried 21 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
"TwoMirCuts was tried 1 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
"ZeroHalf was tried 1 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)\n",
"\n",
"Result - Optimal solution found\n",
"\n",
"Objective value: 10284000.00000000\n",
"Enumerated nodes: 0\n",
"Total iterations: 3\n",
"Time (CPU seconds): 0.01\n",
"Time (Wallclock seconds): 0.01\n",
"\n",
"Total time (CPU seconds): 0.01 (Wallclock seconds): 0.01\n",
"\n"
]
}
],
"source": [
"using Cbc\n",
"using JuMP\n",
"\n",
"# data\n",
"N = 2 # nombre de voitures disponibles\n",
"c = [10000, 9000] # prix de vente par voitures\n",
"b = [15000, 6000, 800] \n",
"A = [10 20 ; 6 5 ; 1 0]\n",
"\n",
"# set optimizer\n",
"model = Model(Cbc.Optimizer)\n",
"\n",
"# define variables\n",
"@variable(model, voitures[1:N] >= 0, integer=true)\n",
"\n",
"# define objective function\n",
"@objective(model, Max, sum(c[i] * voitures[i] for i = 1:N))\n",
"\n",
"# define constraints\n",
"for i = 1:length(b)\n",
" @constraint(model, sum(A[i, j] * voitures[j] for j = 1:N) <= b[i])\n",
"end\n",
"\n",
"println(model)\n",
"\n",
"# run optimization\n",
"optimize!(model)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Solution obtenue:\n",
"\t benefice = 1.0284e7\n",
"\t quantite de voitures 1 = 645.0\n",
"\t quantite de voitures 2 = 426.0\n"
]
}
],
"source": [
"# print solution\n",
"println(\"Solution obtenue:\")\n",
"println(\"\\t benefice = $(objective_value(model))\")\n",
"for i = 1:N\n",
" println(\"\\t quantite de voitures $i = $(value(voitures[i]))\")\n",
"end"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.6.3",
"language": "julia",
"name": "julia-1.6"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Exemple de modèle et résolution du problème de Fabrication du produits"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Project.toml`\n",
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Manifest.toml`\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Project.toml`\n",
"\u001b[32m\u001b[1m No Changes\u001b[22m\u001b[39m to `~/.julia/environments/v1.6/Manifest.toml`\n"
]
}
],
"source": [
"#importer les packages utiles\n",
"import Pkg;\n",
"Pkg.add(\"Cbc\")\n",
"Pkg.add(\"JuMP\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Max 0.07 produits[1] + 0.1 produits[2] + 0.19 produits[3] + 0.12 produits[4] + 0.8 produits[5] + 0.14 produits[6]\n",
"Subject to\n",
" produits[1] + produits[2] + produits[3] + produits[4] + produits[5] + produits[6] = 1.0\n",
" produits[1] + produits[2] ≥ 0.45\n",
" produits[3] + produits[4] ≥ 0.3\n",
" 1.7 produits[1] + 1.2 produits[2] + 3.7 produits[3] + 2.4 produits[4] + 2 produits[5] + 2.9 produits[6] ≤ 2.0\n",
" produits[1] ≤ 0.25\n",
" produits[2] ≤ 0.25\n",
" produits[3] ≤ 0.25\n",
" produits[4] ≤ 0.25\n",
" produits[5] ≤ 0.25\n",
" produits[6] ≤ 0.25\n",
" produits[1] ≥ 0.0\n",
" produits[2] ≥ 0.0\n",
" produits[3] ≥ 0.0\n",
" produits[4] ≥ 0.0\n",
" produits[5] ≥ 0.0\n",
" produits[6] ≥ 0.0\n",
"\n",
"Presolve 4 (-6) rows, 6 (0) columns and 16 (-6) elements\n",
"0 Obj 0.016999999 Primal inf 1.349997 (3) Dual inf 1.419994 (6)\n",
"5 Obj 0.28253846\n",
"Optimal - objective value 0.28253846\n",
"After Postsolve, objective 0.28253846, infeasibilities - dual 0 (0), primal 0 (0)\n",
"Optimal objective 0.2825384615 - 5 iterations time 0.002, Presolve 0.00\n"
]
}
],
"source": [
"using Cbc\n",
"using JuMP\n",
"\n",
"# data\n",
"N = 6 # nombre de produits disponibles\n",
"risques = [1.7 1.2 3.7 2.4 2.0 2.9]\n",
"interets = [ 0.07 0.10 0.19 0.12 0.8 0.14]\n",
"\n",
"# set optimizer\n",
"model = Model(Cbc.Optimizer)\n",
"\n",
"# define variables\n",
"@variable(model, produits[1:N] >= 0)\n",
"\n",
"# define objective function\n",
"@objective(model, Max, sum(interets[i] * produits[i] for i = 1:N))\n",
"\n",
"# define constraints\n",
"@constraint(model, sum(produits[i] for i = 1:N) == 1.0) # somme à 100%\n",
"@constraint(model, sum(produits[i]*risques[i] for i = 1:N) <= 2.0) # risque total\n",
"@constraint(model, produits[1] + produits[2] >= 0.45)\n",
"@constraint(model, produits[3] + produits[4] >= 0.3)\n",
"for i = 1:N\n",
" @constraint(model, produits[i] <= 0.25) # limite de 25%\n",
"end\n",
"\n",
"println(model)\n",
"\n",
"# run optimization\n",
"optimize!(model)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Solution obtenue:\n",
"\t benefice = 0.2825384615384615\n",
"\t quantite de produits 1 = 0.2\n",
"\t quantite de produits 2 = 0.25\n",
"\t quantite de produits 3 = 0.10769230769230764\n",
"\t quantite de produits 4 = 0.19230769230769232\n",
"\t quantite de produits 5 = 0.25\n",
"\t quantite de produits 6 = 0.0\n"
]
}
],
"source": [
"# print solution\n",
"println(\"Solution obtenue:\")\n",
"println(\"\\t benefice = $(objective_value(model))\")\n",
"for i = 1:N\n",
" println(\"\\t quantite de produits $i = $(value(produits[i]))\")\n",
"end"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.6.3",
"language": "julia",
"name": "julia-1.6"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}