{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a77756a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "status:1,Optimal\n",
      "objective:17400000.0\n",
      "A:4000.0\n",
      "AC:0.0\n",
      "AP:4000.0\n",
      "B:3000.0\n",
      "BC:0.0\n",
      "BP:3000.0\n",
      "C:8000.0\n",
      "CC:0.0\n",
      "CP:8000.0\n",
      "D:5000.0\n",
      "DC:5000.0\n",
      "DP:0.0\n",
      "Estampado:-450.0\n",
      "Armado:-1720.0\n",
      "Cableado:-1050.0\n",
      "Ajuste:-1777.77778348\n",
      "Control:-2294.44444812\n",
      "Bal_A:0.0\n",
      "Bal_B:0.0\n",
      "Bal_C:0.0\n",
      "Bal_D:0.0\n",
      "Nec_A:0.0\n",
      "Nec_B:0.0\n",
      "Nec_C:0.0\n",
      "Nec_D:0.0\n"
     ]
    }
   ],
   "source": [
    "#EJERCICIO 2.5\n",
    "#importo librerias \n",
    "from pulp import LpMaximize, LpProblem, LpStatus, lpSum, LpVariable, LpMinimize\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import linprog\n",
    "import numpy as np\n",
    "\n",
    "#Creo el modelo\n",
    "model= LpProblem (name=\"Tableros_autos\", sense=LpMinimize)\n",
    "\n",
    "#Inicializo las variables\n",
    "A=LpVariable(name=\"A\", lowBound=0)\n",
    "AP=LpVariable(name=\"AP\", lowBound=0)\n",
    "AC=LpVariable(name=\"AC\", lowBound=0)\n",
    "B=LpVariable(name=\"B\", lowBound=0)\n",
    "BP=LpVariable(name=\"BP\", lowBound=0)\n",
    "BC=LpVariable(name=\"BC\", lowBound=0)\n",
    "C=LpVariable(name=\"C\", lowBound=0)\n",
    "CP=LpVariable(name=\"CP\", lowBound=0)\n",
    "CC=LpVariable(name=\"CC\", lowBound=0)\n",
    "D=LpVariable(name=\"D\", lowBound=0)\n",
    "DP=LpVariable(name=\"DP\", lowBound=0)\n",
    "DC=LpVariable(name=\"DC\", lowBound=0)\n",
    "\n",
    "model+= (0.05*AP + 0.05*BP + 0.05*CP + 0.05*DP<=1200,\"Estampado\")\n",
    "model+= (0.1*AP + 0.12*BP + 0.14*CP + 0.18*DP<=3600,\"Armado\")\n",
    "model+= (0.2*AP + 0.25*BP + 0.3*CP + 0.25*DP<=5000,\"Cableado\")\n",
    "model+= (0.08888888888*AP + 0.111111111*BP + 0.066666666*CP + 0.11111111111*DP<=3000,\"Ajuste\")\n",
    "model+= (0.02222222222*AP + 0.033333333*BP + 0.033333333*CP + 0.04444444444*DP \n",
    "         + 0.0375* AC + 0.0625* BC + 0.05* CC +0.05*DC<=3000,\"Control\")\n",
    "model+= (-A+AP+AC==0,\"Bal_A\")\n",
    "model+= (-B+BP+BC==0,\"Bal_B\")\n",
    "model+= (-C+CP+CC==0,\"Bal_C\")\n",
    "model+= (-D+DP+DC==0,\"Bal_D\")\n",
    "model+= (A==4000,\"Nec_A\")\n",
    "model+= (B==3000,\"Nec_B\")\n",
    "model+= (C==8000,\"Nec_C\")\n",
    "model+= (D==5000,\"Nec_D\")\n",
    "\n",
    "model+= 500*AP + 600*BP + 1200*CP + 1000*DP + 800*AC +750*BC + 1800*CC + 800*DC\n",
    "\n",
    "#Resolvemos el problema de programacion lineal\n",
    "status = model.solve()\n",
    "\n",
    "#Imprimo la solucion\n",
    "print(f\"status:{model.status},{LpStatus[model.status]}\")#tipo de solucion\n",
    "print(f\"objective:{model.objective.value()}\")#Beneficio maximo sujeto a las restricciones\n",
    "for var in model.variables():\n",
    "    print(f\"{var.name}:{var.value()}\")#Valores de solucion de las variables\n",
    "for name, constraint in model.constraints.items():\n",
    "    print(f\"{name}:{constraint.value()}\") "
   ]
  }
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