001package net.sf.cpsolver.ifs.example.csp;
002
003import java.util.Iterator;
004import java.util.Random;
005
006import net.sf.cpsolver.ifs.model.Constraint;
007import net.sf.cpsolver.ifs.model.Model;
008
009/**
010 * Random Binary CSP with uniform distribution. <br>
011 * <br>
012 * A random CSP is defined by a four-tuple (n, d, p1, p2), where n denotes the
013 * number of variables and d denotes the domain size of each variable, p1 and p2
014 * are two probabilities. They are used to generate randomly the binary
015 * constraints among the variables. p1 represents the probability that a
016 * constraint exists between two different variables and p2 represents the
017 * probability that a pair of values in the domains of two variables connected
018 * by a constraint are incompatible. <br>
019 * <br>
020 * We use a so called model B of Random CSP (n, d, n1, n2) where n1 =
021 * p1*n*(n-1)/2 pairs of variables are randomly and uniformly selected and
022 * binary constraints are posted between them. For each constraint, n2 = p1*d^2
023 * randomly and uniformly selected pairs of values are picked as incompatible.
024 * 
025 * @version IFS 1.2 (Iterative Forward Search)<br>
026 *          Copyright (C) 2006 - 2010 Tomáš Müller<br>
027 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
028 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
029 * <br>
030 *          This library is free software; you can redistribute it and/or modify
031 *          it under the terms of the GNU Lesser General Public License as
032 *          published by the Free Software Foundation; either version 3 of the
033 *          License, or (at your option) any later version. <br>
034 * <br>
035 *          This library is distributed in the hope that it will be useful, but
036 *          WITHOUT ANY WARRANTY; without even the implied warranty of
037 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
038 *          Lesser General Public License for more details. <br>
039 * <br>
040 *          You should have received a copy of the GNU Lesser General Public
041 *          License along with this library; if not see
042 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
043 */
044public class CSPModel extends Model<CSPVariable, CSPValue> {
045
046    /**
047     * Constructor
048     * 
049     * @param nrVariables
050     *            number of variables in the problem
051     * @param nrValues
052     *            number of values of each variable
053     * @param nrConstraints
054     *            number of constraints in the problem
055     * @param nrCompatiblePairs
056     *            number of compatible pairs of values for every constraint
057     * @param seed
058     *            seed for random number generator (use
059     *            {@link System#currentTimeMillis} if not bother)
060     */
061    public CSPModel(int nrVariables, int nrValues, int nrConstraints, int nrCompatiblePairs, long seed) {
062        generate(nrVariables, nrValues, nrConstraints, nrCompatiblePairs, seed);
063    }
064
065    public CSPModel() {
066    }
067
068    private void swap(CSPVariable[][] allPairs, int first, int second) {
069        CSPVariable[] a = allPairs[first];
070        allPairs[first] = allPairs[second];
071        allPairs[second] = a;
072    }
073
074    private void buildBinaryConstraintGraph(Random rnd) {
075        int numberOfAllPairs = variables().size() * (variables().size() - 1) / 2;
076        CSPVariable[][] allPairs = new CSPVariable[numberOfAllPairs][];
077        int idx = 0;
078        for (CSPVariable v1 : variables()) {
079            for (CSPVariable v2 : variables()) {
080                if (v1.getId() >= v2.getId())
081                    continue;
082                allPairs[idx++] = new CSPVariable[] { v1, v2 };
083            }
084        }
085        idx = 0;
086        for (Iterator<Constraint<CSPVariable, CSPValue>> i = constraints().iterator(); i.hasNext();) {
087            CSPBinaryConstraint c = (CSPBinaryConstraint) i.next();
088            swap(allPairs, idx, idx + (int) (rnd.nextDouble() * (numberOfAllPairs - idx)));
089            c.addVariable(allPairs[idx][0]);
090            c.addVariable(allPairs[idx][1]);
091            c.init(rnd);
092            idx++;
093        }
094    }
095
096    private void generate(int nrVariables, int nrValues, int nrConstraints, int nrCompatiblePairs, long seed) {
097        Random rnd = new Random(seed);
098
099        for (int i = 0; i < nrVariables; i++) {
100            CSPVariable var = new CSPVariable(i + 1, nrValues);
101            addVariable(var);
102        }
103
104        for (int i = 0; i < nrConstraints; i++) {
105            CSPBinaryConstraint c = new CSPBinaryConstraint(i + 1, nrCompatiblePairs);
106            addConstraint(c);
107        }
108
109        buildBinaryConstraintGraph(rnd);
110    }
111}