// // Copyright 2012 Hakan Kjellerstrand // // 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. using System; using System.Collections; using System.IO; using System.Text.RegularExpressions; using Google.OrTools.ConstraintSolver; public class SetCovering4 { /** * * Solves a set covering problem. * See See http://www.hakank.org/or-tools/set_covering4.py * */ private static void Solve(int set_partition) { Solver solver = new Solver("SetCovering4"); // // data // // Set partition and set covering problem from // Example from the Swedish book // Lundgren, Roennqvist, Vaebrand // 'Optimeringslaera' (translation: 'Optimization theory'), // page 408. int num_alternatives = 10; int num_objects = 8; // costs for the alternatives int[] costs = {19, 16, 18, 13, 15, 19, 15, 17, 16, 15}; // the alternatives, and their objects int[,] a = { // 1 2 3 4 5 6 7 8 the objects {1,0,0,0,0,1,0,0}, // alternative 1 {0,1,0,0,0,1,0,1}, // alternative 2 {1,0,0,1,0,0,1,0}, // alternative 3 {0,1,1,0,1,0,0,0}, // alternative 4 {0,1,0,0,1,0,0,0}, // alternative 5 {0,1,1,0,0,0,0,0}, // alternative 6 {0,1,1,1,0,0,0,0}, // alternative 7 {0,0,0,1,1,0,0,1}, // alternative 8 {0,0,1,0,0,1,0,1}, // alternative 9 {1,0,0,0,0,1,1,0}}; // alternative 10 // // Decision variables // IntVar[] x = solver.MakeIntVarArray(num_alternatives, 0, 1, "x"); // number of assigned senators, to be minimized IntVar z = x.ScalProd(costs).VarWithName("z"); // // Constraints // for(int j = 0; j < num_objects; j++) { IntVar[] b = new IntVar[num_alternatives]; for(int i = 0; i < num_alternatives; i++) { b[i] = (x[i] * a[i,j]).Var(); } if (set_partition == 1) { solver.Add(b.Sum() >= 1); } else { solver.Add(b.Sum() == 1); } } // // objective // OptimizeVar objective = z.Minimize(1); // // Search // DecisionBuilder db = solver.MakePhase(x, Solver.INT_VAR_DEFAULT, Solver.INT_VALUE_DEFAULT); solver.NewSearch(db, objective); while (solver.NextSolution()) { Console.WriteLine("z: " + z.Value()); Console.Write("Selected alternatives: "); for(int i = 0; i < num_alternatives; i++) { if (x[i].Value() == 1) { Console.Write((i+1) + " "); } } Console.WriteLine("\n"); } Console.WriteLine("\nSolutions: {0}", solver.Solutions()); Console.WriteLine("WallTime: {0}ms", solver.WallTime()); Console.WriteLine("Failures: {0}", solver.Failures()); Console.WriteLine("Branches: {0} ", solver.Branches()); solver.EndSearch(); } public static void Main(String[] args) { Console.WriteLine("Set partition:"); Solve(1); Console.WriteLine("\nSet covering:"); Solve(0); } }