learning PuLP

learning_pulp

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  "name": ""
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  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!pip install pulp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Downloading/unpacking pulp\n",
        "  Running setup.py (path:c:\\users\\ddye\\appdata\\local\\temp\\pip_build_ddye\\pulp\\setup.py) egg_info for package pulp\n",
        "    \n",
        "Requirement already satisfied (use --upgrade to upgrade): pyparsing<=1.9.9 in c:\\users\\ddye\\appdata\\local\\continuum\\anaconda\\lib\\site-packages (from pulp)\n",
        "Installing collected packages: pulp\n",
        "  Running setup.py install for pulp\n",
        "    \n",
        "    Installing pulpdoctest-script.py script to C:\\Users\\ddye\\AppData\\Local\\Continuum\\Anaconda\\Scripts\n",
        "    Installing pulpdoctest.exe script to C:\\Users\\ddye\\AppData\\Local\\Continuum\\Anaconda\\Scripts\n",
        "    Installing pulptest-script.py script to C:\\Users\\ddye\\AppData\\Local\\Continuum\\Anaconda\\Scripts\n",
        "    Installing pulptest.exe script to C:\\Users\\ddye\\AppData\\Local\\Continuum\\Anaconda\\Scripts\n",
        "Successfully installed pulp\n",
        "Cleaning up...\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pulp\n",
      "pulp.pulpTestAll()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\t Testing zero subtraction\n",
        "\t Testing continuous LP solution\n",
        "\t Testing maximize continuous LP solution"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing unbounded continuous LP solution"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing Long Names"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing repeated Names"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing zero constraint\n",
        "\t Testing zero objective"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing LpVariable (not LpAffineExpression) objective"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing MIP solution"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing MIP relaxation"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing feasibility problem (no objective)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing an infeasible problem"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing an integer infeasible problem\n",
        "\t Testing column based modelling"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing dual variables and slacks reporting\n",
        "\t Testing fractional constraints"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing elastic constraints (no change)\n",
        "\t Testing elastic constraints (freebound)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "\t Testing elastic constraints (penalty unchanged)\n",
        "\t Testing elastic constraints (penalty unbounded)"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "* Solver pulp.solvers.PULP_CBC_CMD passed.\n",
        "Solver pulp.solvers.CPLEX_DLL unavailable\n",
        "Solver pulp.solvers.CPLEX_CMD unavailable\n",
        "Solver pulp.solvers.CPLEX_PY unavailable\n",
        "Solver pulp.solvers.COIN_CMD unavailable\n",
        "Solver pulp.solvers.COINMP_DLL unavailable\n",
        "Solver pulp.solvers.GLPK_CMD unavailable\n",
        "Solver pulp.solvers.XPRESS unavailable\n",
        "Solver pulp.solvers.GUROBI unavailable\n",
        "Solver pulp.solvers.GUROBI_CMD unavailable\n",
        "Solver pulp.solvers.PYGLPK unavailable\n",
        "Solver pulp.solvers.YAPOSIB unavailable\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Creates the 'prob' variable to contain the problem data    \n",
      "prob = pulp.LpProblem(\"Egg Cheese Mix Problem\", pulp.LpMaximize)\n",
      "\n",
      "eggs = pulp.LpVariable('eggs', lowBound = 1, upBound = 4, cat='Integer')\n",
      "cheese = pulp.LpVariable('cheese',lowBound = .33, upBound = 1, cat='Continuous')\n",
      "\n",
      "# Creates the objective function\n",
      "prob += pulp.lpSum([eggs*70 + cheese*110*3]), \"Total Calories\"\n",
      "\n",
      "# Objective function: keep calories under 350. Each egg is 70 calories. Each 1/3 cup of cheese is 110 calories\n",
      "prob += pulp.lpSum([eggs*70 + cheese*110*3]) <= 350., \"MaxCalorie\"\n",
      "\n",
      "prob += (pulp.lpSum([eggs/2.]) >= pulp.lpSum([cheese/.33])*.75), \"Min Cheese Ratio: at least .75*1/3 cup for every 2 eggs\"\n",
      "\n",
      "prob += (pulp.lpSum([eggs/2.]) <= pulp.lpSum([cheese/.33])*1.25), \"Max Cheese Ratio: at most 1.25*1/3 cup for every 2 eggs\"\n",
      "\n",
      "# The problem data is written to an .lp file\n",
      "prob.writeLP(\"EggCheeseMix.lp\")\n",
      "\n",
      "# The problem is solved using PuLP's choice of Solver\n",
      "prob.solve()\n",
      "\n",
      "# The status of the solution is printed to the screen\n",
      "print(\"Status:\", pulp.LpStatus[prob.status])\n",
      "\n",
      "# Each of the variables is printed with it's resolved optimum value\n",
      "for v in prob.variables():\n",
      "    print(v.name, \"=\", v.varValue)\n",
      "\n",
      "# The optimised objective function value is printed to the screen    \n",
      "print(\"Total Calories= \", pulp.value(prob.objective))\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "('Status:', 'Optimal')\n",
        "('cheese', '=', 0.42424242)\n",
        "('eggs', '=', 3.0)\n",
        "('Total Calories= ', 349.9999986)\n"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}