// 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. package com.google.ortools.examples; import com.google.ortools.constraintsolver.DecisionBuilder; import com.google.ortools.constraintsolver.IntVar; import com.google.ortools.constraintsolver.OptimizeVar; import com.google.ortools.constraintsolver.Solver; import java.io.*; import java.text.*; import java.util.*; public class SetCovering4 { static { System.loadLibrary("jniortools"); } /** Solves a set covering problem. See http://www.hakank.org/google_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 // // variables // IntVar[] x = solver.makeIntVarArray(num_alternatives, 0, 1, "x"); // number of assigned senators, to be minimize IntVar z = solver.makeScalProd(x, costs).var(); // // 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] = solver.makeProd(x[i], a[i][j]).var(); } if (set_partition == 1) { solver.addConstraint(solver.makeSumGreaterOrEqual(b, 1)); } else { solver.addConstraint(solver.makeSumEquality(b, 1)); } } // // objective // OptimizeVar objective = solver.makeMinimize(z, 1); // // search // DecisionBuilder db = solver.makePhase(x, solver.INT_VAR_DEFAULT, solver.INT_VALUE_DEFAULT); solver.newSearch(db, objective); // // output // while (solver.nextSolution()) { System.out.println("z: " + z.value()); System.out.print("Selected alternatives: "); for (int i = 0; i < num_alternatives; i++) { if (x[i].value() == 1) { System.out.print((1 + i) + " "); } } System.out.println("\n"); } solver.endSearch(); // Statistics System.out.println(); System.out.println("Solutions: " + solver.solutions()); System.out.println("Failures: " + solver.failures()); System.out.println("Branches: " + solver.branches()); System.out.println("Wall time: " + solver.wallTime() + "ms"); } public static void main(String[] args) throws Exception { System.out.println("Set partition:"); SetCovering4.solve(1); System.out.println("\nSet covering:"); SetCovering4.solve(0); } }