{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import sys\n",
    "#!{sys.executable} -m pip install ortools \n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "import random\n",
    "from ortools.linear_solver import pywraplp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "InputData = pd.read_excel(\"Nutrition Info.xlsx\", sep=\"\\t\")\n",
    "InputData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "PrefData = pd.read_excel(\"Nutrition Preferences.xlsx\", sep=\"\\t\")\n",
    "PrefData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine the start time\n",
    "StartTime = time.process_time()\n",
    "\n",
    "# Define our Linear Program\n",
    "Solver = pywraplp.Solver('Solver', pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)\n",
    "\n",
    "# Define the Preference Coefficient P[i,j] for Shiva, for Ingredient i used for Meal j\n",
    "n=19\n",
    "m=5\n",
    "\n",
    "P = np.zeros(shape=(n, m), dtype=int)\n",
    "blocks = [\"MON\", \"TUE\", \"WED\", \"THU\", \"FRI\"]\n",
    "\n",
    "for j in range(m):\n",
    "    for i in range(n):\n",
    "        P[i,j] = PrefData[\"Shiva\"][i]\n",
    "        \n",
    "# Define the variable X[i,j], which will equal the number of times Ingredient i is used for Meal j\n",
    "# No ingredient can be used more than twice.\n",
    "X = {}\n",
    "for i in range(n):\n",
    "    for j in range(m):\n",
    "        X[i,j] = Solver.IntVar(0, 2, 'X[%d, %d]' % (i,j))\n",
    "        \n",
    "# Set up our Happiness Function for SHIVA, which maximizes the total number of Happiness Points\n",
    "HappinessFunction = Solver.Sum(P[i,j]*X[i,j] for i in range(n) for j in range(m))\n",
    "Solver.Maximize(HappinessFunction)\n",
    "\n",
    "# Include our first constraint: Each meal must have at least 700 calories\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Calories\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               InputData[\"Calories\"][19] )\n",
    "                 \n",
    "# Include our second constraint: Each meal must have at most 24 grams of fat\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Fat\"][i]*X[i,j] for i in range(n)]) <=\n",
    "               InputData[\"Fat\"][19] )\n",
    "                 \n",
    "# Include our third constraint: Each meal must have at most 3 grams of sodium\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Sodium\"][i]*X[i,j] for i in range(n)]) <=\n",
    "               InputData[\"Sodium\"][19] )\n",
    "\n",
    "# Include our fourth constraint: Each meal must have at least 90 grams of carbs\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Carbs\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               1*InputData[\"Carbs\"][19] )\n",
    "    \n",
    "# Include our fifth constraint: Each meal must have at least 8 grams of dietary fiber\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Fiber\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               1*InputData[\"Fiber\"][19] )\n",
    "\n",
    "# Include our sixth constraint: Each meal must have at least 17 grams of protein\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Protein\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               1*InputData[\"Protein\"][19] )\n",
    "\n",
    "# Include our seventh constraints: no beef, no ham, no salami,\n",
    "# and also, at most one serving of chicken in any two day stretch\n",
    "\n",
    "Solver.Add(X[11,0]+X[12,0]+X[15,0]==0)\n",
    "Solver.Add(X[11,1]+X[12,1]+X[15,1]==0)\n",
    "Solver.Add(X[11,2]+X[12,2]+X[15,2]==0)\n",
    "Solver.Add(X[11,3]+X[12,3]+X[15,3]==0)\n",
    "Solver.Add(X[11,4]+X[12,4]+X[15,4]==0)\n",
    "Solver.Add(X[13,0]+X[14,0]+X[13,1]+X[14,1]<=1)\n",
    "Solver.Add(X[13,1]+X[14,1]+X[13,2]+X[14,2]<=1)\n",
    "Solver.Add(X[13,2]+X[14,2]+X[13,3]+X[14,3]<=1)\n",
    "Solver.Add(X[13,3]+X[14,3]+X[13,4]+X[14,4]<=1)\n",
    "\n",
    "\n",
    "\n",
    "# Include our final constraint: Each meal must have at least 6 ingredients and at most 10 \n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([X[i,j] for i in range(n)]) >= 6)\n",
    "    Solver.Add(Solver.Sum([X[i,j] for i in range(n)]) <= 10)\n",
    "\n",
    "# Solve the Integer Linear program\n",
    "Output = Solver.Solve()\n",
    "TotalPoints = round(Solver.Objective().Value())\n",
    "\n",
    "# Determine the total time of running the program.\n",
    "TotalTime = round(time.process_time() - StartTime, 4)\n",
    "\n",
    "# Output one of the possible optimal solutions.\n",
    "print(\"Python returns a solution with\", TotalPoints, \"Total Happiness Points in\",\n",
    "      TotalTime, \"seconds\")\n",
    "print()\n",
    "print(\"Shiva's menu\")\n",
    "for j in range(m):\n",
    "    print()\n",
    "    for i in range(n):\n",
    "        if X[i,j].solution_value()==1:\n",
    "            print(\"The meal on\", blocks[j], \"will have one serving of\", \n",
    "                  InputData[\"Ingredient\"][i], \"with score\", P[i,j])\n",
    "        if X[i,j].solution_value()==2:\n",
    "            print(\"The meal on\", blocks[j], \"will have two servings of\", \n",
    "                  InputData[\"Ingredient\"][i], \"with score\", P[i,j])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine the start time\n",
    "StartTime = time.process_time()\n",
    "\n",
    "# Define our Linear Program\n",
    "Solver = pywraplp.Solver('Solver', pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)\n",
    "\n",
    "# Define the Preference Coefficient P[i,j] for DP, for Ingredient i used for Meal j\n",
    "n=19\n",
    "m=5\n",
    "\n",
    "P = np.zeros(shape=(n, m), dtype=int)\n",
    "blocks = [\"MON\", \"TUE\", \"WED\", \"THU\", \"FRI\"]\n",
    "\n",
    "for j in range(m):\n",
    "    for i in range(n):\n",
    "        P[i,j] = PrefData[\"DP\"][i]\n",
    "        \n",
    "# Define the variable X[i,j], which will equal the number of times Ingredient i is used for Meal j\n",
    "# No ingredient can be used more than twice.\n",
    "X = {}\n",
    "for i in range(n):\n",
    "    for j in range(m):\n",
    "        X[i,j] = Solver.IntVar(0, 2, 'X[%d, %d]' % (i,j))\n",
    "        \n",
    "# Set up our Happiness Function for DP, which maximizes the total number of Happiness Points\n",
    "HappinessFunction = Solver.Sum(P[i,j]*X[i,j] for i in range(n) for j in range(m))\n",
    "Solver.Maximize(HappinessFunction)\n",
    "\n",
    "# Include our first constraint: Each meal must have at least 700 calories\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Calories\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               InputData[\"Calories\"][19] )\n",
    "                 \n",
    "# Include our second constraint: Each meal must have at most 24 grams of fat\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Fat\"][i]*X[i,j] for i in range(n)]) <=\n",
    "               InputData[\"Fat\"][19] )\n",
    "                 \n",
    "# Include our third constraint: Each meal must have at most 3 grams of sodium\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Sodium\"][i]*X[i,j] for i in range(n)]) <=\n",
    "               InputData[\"Sodium\"][19] )\n",
    "\n",
    "# Include our fourth constraint: Each meal must have at least 90 grams of carbs\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Carbs\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               1*InputData[\"Carbs\"][19] )\n",
    "    \n",
    "# Include our fifth constraint: Each meal must have at least 8 grams of dietary fiber\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Fiber\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               1*InputData[\"Fiber\"][19] )\n",
    "\n",
    "# Include our sixth constraint: Each meal must have at least 17 grams of protein\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([InputData[\"Protein\"][i]*X[i,j] for i in range(n)]) >=\n",
    "               1*InputData[\"Protein\"][19] )\n",
    "\n",
    "# Include our seventh constraints: one serving of fries on Wednesday and Friday, \n",
    "# no spinach and cabbage together, and no chicken on Fridays\n",
    "for j in range(m):\n",
    "    Solver.Add(X[17,2]==1)\n",
    "    Solver.Add(X[17,4]==1)\n",
    "    Solver.Add(X[1,j]+X[4,j]<=1)\n",
    "    Solver.Add(X[13,4]+X[14,4]==0)\n",
    "    \n",
    "# Include our final constraint: Each meal must have at least 6 ingredients and at most 10.\n",
    "for j in range(m):\n",
    "    Solver.Add(Solver.Sum([X[i,j] for i in range(n)]) >= 6)\n",
    "    Solver.Add(Solver.Sum([X[i,j] for i in range(n)]) <= 10)\n",
    "    \n",
    "\n",
    "# Solve the Integer Linear program\n",
    "Output = Solver.Solve()\n",
    "TotalPoints = round(Solver.Objective().Value())\n",
    "\n",
    "# Determine the total time of running the program.\n",
    "TotalTime = round(time.process_time() - StartTime, 4)\n",
    "\n",
    "# Output one of the possible optimal solutions.\n",
    "print(\"Python returns a solution with\", TotalPoints, \"Total Happiness Points in\",\n",
    "      TotalTime, \"seconds\")\n",
    "print()\n",
    "print(\"DP's menu\")\n",
    "for j in range(m):\n",
    "    print()\n",
    "    for i in range(n):\n",
    "        if X[i,j].solution_value()==1:\n",
    "            print(\"The meal on\", blocks[j], \"will have one serving of\", \n",
    "                  InputData[\"Ingredient\"][i], \"with score\", P[i,j])\n",
    "        if X[i,j].solution_value()==2:\n",
    "            print(\"The meal on\", blocks[j], \"will have two servings of\", \n",
    "                  InputData[\"Ingredient\"][i], \"with score\", P[i,j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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