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diet2.py


diet2.py


#!/usr/bin/python

# Copyright 2017, Gurobi Optimization, Inc.

# Separate the model (dietmodel.py) from the data file (diet2.py), so
# that the model can be solved with different data files.
#
# Nutrition guidelines, based on
# USDA Dietary Guidelines for Americans, 2005
# http://www.health.gov/DietaryGuidelines/dga2005/

from gurobipy import *

categories, minNutrition, maxNutrition = multidict({
  'calories': [1800, 2200],
  'protein':  [91, GRB.INFINITY],
  'fat':      [0, 65],
  'sodium':   [0, 1779] })

foods, cost = multidict({
  'hamburger': 2.49,
  'chicken':   2.89,
  'hot dog':   1.50,
  'fries':     1.89,
  'macaroni':  2.09,
  'pizza':     1.99,
  'salad':     2.49,
  'milk':      0.89,
  'ice cream': 1.59 })

# Nutrition values for the foods
nutritionValues = {
  ('hamburger', 'calories'): 410,
  ('hamburger', 'protein'):  24,
  ('hamburger', 'fat'):      26,
  ('hamburger', 'sodium'):   730,
  ('chicken',   'calories'): 420,
  ('chicken',   'protein'):  32,
  ('chicken',   'fat'):      10,
  ('chicken',   'sodium'):   1190,
  ('hot dog',   'calories'): 560,
  ('hot dog',   'protein'):  20,
  ('hot dog',   'fat'):      32,
  ('hot dog',   'sodium'):   1800,
  ('fries',     'calories'): 380,
  ('fries',     'protein'):  4,
  ('fries',     'fat'):      19,
  ('fries',     'sodium'):   270,
  ('macaroni',  'calories'): 320,
  ('macaroni',  'protein'):  12,
  ('macaroni',  'fat'):      10,
  ('macaroni',  'sodium'):   930,
  ('pizza',     'calories'): 320,
  ('pizza',     'protein'):  15,
  ('pizza',     'fat'):      12,
  ('pizza',     'sodium'):   820,
  ('salad',     'calories'): 320,
  ('salad',     'protein'):  31,
  ('salad',     'fat'):      12,
  ('salad',     'sodium'):   1230,
  ('milk',      'calories'): 100,
  ('milk',      'protein'):  8,
  ('milk',      'fat'):      2.5,
  ('milk',      'sodium'):   125,
  ('ice cream', 'calories'): 330,
  ('ice cream', 'protein'):  8,
  ('ice cream', 'fat'):      10,
  ('ice cream', 'sodium'):   180 }

import dietmodel
dietmodel.solve(categories, minNutrition, maxNutrition,
                foods, cost, nutritionValues)