# Copyright 2010 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. """ Assignment problem in Google CP Solver. Winston 'Operations Research', Assignment Problems, page 393f (generalized version with added test column) Compare with the following models: * Comet : http://www.hakank.org/comet/assignment.co * ECLiPSE : http://www.hakank.org/eclipse/assignment.ecl * Gecode : http://www.hakank.org/gecode/assignment.cpp * MiniZinc: http://www.hakank.org/minizinc/assignment.mzn * Tailor/Essence': http://www.hakank.org/tailor/assignment.eprime * SICStus: http://hakank.org/sicstus/assignment.pl 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 from ortools.constraint_solver import pywrapcp def main(cost, rows, cols): # Create the solver. solver = pywrapcp.Solver("n-queens") # # data # # declare variables total_cost = solver.IntVar(0, 100, "total_cost") x = [] for i in range(rows): t = [] for j in range(cols): t.append(solver.IntVar(0, 1, "x[%i,%i]" % (i, j))) x.append(t) x_flat = [x[i][j] for i in range(rows) for j in range(cols)] # # constraints # # total_cost solver.Add(total_cost == solver.Sum( [solver.ScalProd(x_row, cost_row) for (x_row, cost_row) in zip(x, cost)])) # exacly one assignment per row, all rows must be assigned [ solver.Add(solver.Sum([x[row][j] for j in range(cols)]) == 1) for row in range(rows) ] # zero or one assignments per column [ solver.Add(solver.Sum([x[i][col] for i in range(rows)]) <= 1) for col in range(cols) ] objective = solver.Minimize(total_cost, 1) # # solution and search # solution = solver.Assignment() solution.Add(x_flat) solution.Add(total_cost) # db: DecisionBuilder db = solver.Phase(x_flat, solver.INT_VAR_SIMPLE, solver.ASSIGN_MIN_VALUE) solver.NewSearch(db, [objective]) num_solutions = 0 while solver.NextSolution(): print("total_cost:", total_cost.Value()) for i in range(rows): for j in range(cols): print(x[i][j].Value(), end=" ") print() print() for i in range(rows): print("Task:", i, end=" ") for j in range(cols): if x[i][j].Value() == 1: print(" is done by ", j) print() num_solutions += 1 solver.EndSearch() print() print("num_solutions:", num_solutions) print("failures:", solver.Failures()) print("branches:", solver.Branches()) print("WallTime:", solver.WallTime()) # Problem instance # hakank: I added the fifth column to make it more # interesting rows = 4 cols = 5 cost = [[14, 5, 8, 7, 15], [2, 12, 6, 5, 3], [7, 8, 3, 9, 7], [2, 4, 6, 10, 1]] if __name__ == "__main__": main(cost, rows, cols)