text: # Copyright 2011 Hakan Kjellerstrand hakank@bonetmail.com
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """
  
    Volsay problem in Google or-tools.
  
    From the OPL model volsay.mod
    Using arrays.
  
    This model was created by Hakan Kjellerstrand (hakank@bonetmail.com)
    Also see my other Google CP Solver models:
    http://www.hakank.org/google_or_tools/
  """
  from __future__ import print_function
  from ortools.linear_solver import pywraplp
  
  
  def main(unused_argv):
  
    # Create the solver.
  
    # using GLPK
    # solver = pywraplp.Solver('CoinsGridGLPK',
    #                          pywraplp.Solver.GLPK_LINEAR_PROGRAMMING)
  
    # Using CLP
    solver = pywraplp.Solver('CoinsGridCLP',
                             pywraplp.Solver.CLP_LINEAR_PROGRAMMING)
  
    # data
    num_products = 2
    Gas = 0
    Chloride = 1
  
    products = ['Gas', 'Chloride']
  
    # declare variables
    production = [solver.NumVar(0, 100000, 'production[%i]' % i)
                  for i in range(num_products)]
  
    #
    # constraints
    #
    solver.Add(production[Gas] + production[Chloride] <= 50)
    solver.Add(3 * production[Gas] + 4 * production[Chloride] <= 180)
  
    # objective
    objective = solver.Maximize(40 * production[Gas] + 50 * production[Chloride])
  
    print('NumConstraints:', solver.NumConstraints())
  
    #
    # solution and search
    #
    solver.Solve()
  
    print()
    print('objective = ', solver.Objective().Value())
    for i in range(num_products):
      print(products[i], '=', production[i].SolutionValue(), end=' ')
      print('ReducedCost = ', production[i].ReducedCost())
  
  if __name__ == '__main__':
    main('Volsay')
  