# Copyright 2010 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. """ 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@bonetmail.com) Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/ """ from 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(), print print for i in range(rows): print "Task:",i, 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)