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SetCovering4.java
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SetCovering4.java
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// Copyright 2011 Hakan Kjellerstrand [email protected]
// 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.contrib;
import com.google.ortools.Loader;
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 {
/** 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 {
Loader.loadNativeLibraries();
System.out.println("Set partition:");
SetCovering4.solve(1);
System.out.println("\nSet covering:");
SetCovering4.solve(0);
}
}