org.chocosolver.samples.integer.GolombRuler Maven / Gradle / Ivy

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/**
 * Copyright (c) 2015, Ecole des Mines de Nantes
 * All rights reserved.
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 *    This product includes software developed by the .
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 *    derived from this software without specific prior written permission.
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package org.chocosolver.samples.integer;

import org.chocosolver.samples.AbstractProblem;
import org.chocosolver.solver.ResolutionPolicy;
import org.chocosolver.solver.Solver;
import org.chocosolver.solver.constraints.Constraint;
import org.chocosolver.solver.constraints.IntConstraintFactory;
import org.chocosolver.solver.search.strategy.IntStrategyFactory;
import org.chocosolver.solver.variables.IntVar;
import org.chocosolver.solver.variables.VariableFactory;
import org.kohsuke.args4j.Option;

/**
 * CSPLib prob006:

 * A Golomb ruler may be defined as a set of m integers 0 = a_1 < a_2 < ... < a_m such that
 * the m(m-1)/2 differences a_j - a_i, 1 <= i < j <= m are distinct.
 * Such a ruler is said to contain m marks and is of length a_m.
 * 

 * The objective is to find optimal (minimum length) or near optimal rulers.
 * 

 *
 * @author Charles Prud'homme
 * @since 31/03/11
 */
public class GolombRuler extends AbstractProblem {

    @Option(name = "-m", usage = "Golomb ruler order.", required = false)
    private int m = 10;

    IntVar[] ticks;
    IntVar[] diffs;
    IntVar[][] m_diffs;

    Constraint[] lex;
    Constraint alldiff;
    Constraint[] distances;

    @Override
    public void createSolver() {
        solver = new Solver("Golomb Ruler");
    }

    @Override
    public void buildModel() {
        ticks = VariableFactory.enumeratedArray("a", m, 0, ((m < 31) ? (1 << (m + 1)) - 1 : 9999), solver);

        solver.post(IntConstraintFactory.arithm(ticks[0], "=", 0));

        lex = new Constraint[m - 1];
        for (int i = 0; i < m - 1; i++) {
            lex[i] = IntConstraintFactory.arithm(ticks[i + 1], ">", ticks[i]);
        }
        solver.post(lex);

        diffs = VariableFactory.enumeratedArray("d", (m * m - m) / 2, 0, ((m < 31) ? (1 << (m + 1)) - 1 : 9999), solver);
        m_diffs = new IntVar[m][m];
        distances = new Constraint[(m * m - m) / 2];
        for (int k = 0, i = 0; i < m - 1; i++) {
            for (int j = i + 1; j < m; j++, k++) {
                // d[k] is m[j]-m[i] and must be at least sum of first j-i integers
                //  it is worth adding a constraint instead of a view
                distances[k] = IntConstraintFactory.scalar(new IntVar[]{ticks[j], ticks[i]}, new int[]{1, -1}, diffs[k]);
                solver.post(distances[k]);
                solver.post(IntConstraintFactory.arithm(diffs[k], ">=", (j - i) * (j - i + 1) / 2));
                solver.post(IntConstraintFactory.arithm(diffs[k], "-", ticks[m - 1], "<=", -((m - 1 - j + i) * (m - j + i)) / 2));
                solver.post(IntConstraintFactory.arithm(diffs[k], "<=", ticks[m - 1], "-", ((m - 1 - j + i) * (m - j + i)) / 2));
                m_diffs[i][j] = diffs[k];
            }
        }
        alldiff = IntConstraintFactory.alldifferent(diffs, "BC");
        solver.post(alldiff);

        // break symetries
        if (m > 2) {
            solver.post(IntConstraintFactory.arithm(diffs[0], "<", diffs[diffs.length - 1]));
        }
    }

    @Override
    public void configureSearch() {
        solver.set(IntStrategyFactory.lexico_LB(ticks));
    }

    @Override
    public void solve() {
        solver.findOptimalSolution(ResolutionPolicy.MINIMIZE, (IntVar) solver.getVars()[m - 1]);
    }

    @Override
    public void prettyOut() {
    }

    public static void main(String[] args) {
        new GolombRuler().execute(args);
    }
}