# Copyright 2011 Hakan Kjellerstrand hakank@gmail.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. """ Knapsack problem using MIP in Google or-tools. From the OPL model knapsack.mod This model was created by Hakan Kjellerstrand (hakank@gmail.com) Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/ """ from __future__ import print_function import sys from ortools.linear_solver import pywraplp def main(sol='CBC'): # Create the solver. print('Solver: ', sol) # using GLPK if sol == 'GLPK': solver = pywraplp.Solver('CoinsGridGLPK', pywraplp.Solver.GLPK_MIXED_INTEGER_PROGRAMMING) else: # Using CBC solver = pywraplp.Solver('CoinsGridCBC', pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING) # # data # nb_items = 12 nb_resources = 7 items = list(range(nb_items)) resources = list(range(nb_resources)) capacity = [18209, 7692, 1333, 924, 26638, 61188, 13360] value = [96, 76, 56, 11, 86, 10, 66, 86, 83, 12, 9, 81] use = [[19, 1, 10, 1, 1, 14, 152, 11, 1, 1, 1, 1], [0, 4, 53, 0, 0, 80, 0, 4, 5, 0, 0, 0], [4, 660, 3, 0, 30, 0, 3, 0, 4, 90, 0, 0], [7, 0, 18, 6, 770, 330, 7, 0, 0, 6, 0, 0], [0, 20, 0, 4, 52, 3, 0, 0, 0, 5, 4, 0], [0, 0, 40, 70, 4, 63, 0, 0, 60, 0, 4, 0], [0, 32, 0, 0, 0, 5, 0, 3, 0, 660, 0, 9]] max_value = max(capacity) # # variables # take = [solver.IntVar(0, max_value, 'take[%i]' % j) for j in items] # total cost, to be maximized z = solver.Sum([value[i] * take[i] for i in items]) # # constraints # for r in resources: solver.Add(solver.Sum([use[r][i] * take[i] for i in items]) <= capacity[r]) # objective objective = solver.Maximize(z) # # solution and search # solver.Solve() print() print('z: ', int(solver.Objective().Value())) print('take:', end=' ') for i in items: print(int(take[i].SolutionValue()), end=' ') print() print() print('walltime :', solver.WallTime(), 'ms') if sol == 'CBC': print('iterations:', solver.Iterations()) if __name__ == '__main__': sol = 'CBC' if len(sys.argv) > 1: sol = sys.argv[1] if sol != 'GLPK' and sol != 'CBC': print('Solver must be either GLPK or CBC') sys.exit(1) main(sol)