    001package net.sf.cpsolver.ifs.algorithms;
    002
    003import net.sf.cpsolver.ifs.heuristics.NeighbourSelection;
    004import net.sf.cpsolver.ifs.model.Model;
    005import net.sf.cpsolver.ifs.model.Neighbour;
    006import net.sf.cpsolver.ifs.model.Value;
    007import net.sf.cpsolver.ifs.model.Variable;
    008import net.sf.cpsolver.ifs.solution.Solution;
    009import net.sf.cpsolver.ifs.solver.Solver;
    010import net.sf.cpsolver.ifs.util.DataProperties;
    011
    012/**
    013 * Hill climber. In each iteration, one of the given neighbourhoods is selected first,
    014 * then a neighbour is generated and it is accepted if its value
    015 * {@link Neighbour#value()} is below or equal to zero. The search is
    016 * stopped after a given amount of idle iterations ( can be defined by problem
    017 * property HillClimber.MaxIdle). <br>
    018 * <br>
    019 * Custom neighbours can be set using HillClimber.Neighbours property that should
    020 * contain semicolon separated list of {@link NeighbourSelection}. By default,
    021 * each neighbour selection is selected with the same probability (each has 1 point in
    022 * a roulette wheel selection). It can be changed by adding &nbsp;@n at the end
    023 * of the name of the class, for example:<br>
    024 * <code>
    025 * HillClimber.Neighbours=net.sf.cpsolver.ifs.algorithms.neighbourhoods.RandomMove;net.sf.cpsolver.ifs.algorithms.neighbourhoods.RandomSwapMove@0.1
    026 * </code>
    027 * <br>
    028 * Selector RandomSwapMove is 10&times; less probable to be selected than other selectors.
    029 * When HillClimber.Random is true, all selectors are selected with the same probability, ignoring these weights.
    030 * <br><br>
    031 * When HillClimber.Update is true, {@link NeighbourSelector#update(Neighbour, long)} is called
    032 * after each iteration (on the selector that was used) and roulette wheel selection
    033 * that is using {@link NeighbourSelector#getPoints()} is used to pick a selector in each iteration.
    034 * See {@link NeighbourSelector} for more details.
    035 * <br>
    036 *
    037 * @version IFS 1.2 (Iterative Forward Search)<br>
    038 *          Copyright (C) 2014 Tomáš Müller<br>
    039 *          <a href="mailto:muller@unitime.org">muller@unitime.org</a><br>
    040 *          <a href="http://muller.unitime.org">http://muller.unitime.org</a><br>
    041 * <br>
    042 *          This library is free software; you can redistribute it and/or modify
    043 *          it under the terms of the GNU Lesser General Public License as
    044 *          published by the Free Software Foundation; either version 3 of the
    045 *          License, or (at your option) any later version. <br>
    046 * <br>
    047 *          This library is distributed in the hope that it will be useful, but
    048 *          WITHOUT ANY WARRANTY; without even the implied warranty of
    049 *          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
    050 *          Lesser General Public License for more details. <br>
    051 * <br>
    052 *          You should have received a copy of the GNU Lesser General Public
    053 *          License along with this library; if not see
    054 *          <a href='http://www.gnu.org/licenses/'>http://www.gnu.org/licenses/</a>.
    055 */
    056public class HillClimber<V extends Variable<V, T>, T extends Value<V, T>> extends NeighbourSearch<V, T> {
    057    protected int iMaxIdleIters = 10000;
    058    protected int iLastImprovingIter = 0;
    059    protected double iBestValue = 0;
    060    protected boolean iSetHCMode = false;
    061
    062    /**
    063     * Constructor
    064     * <ul>
    065     * <li>HillClimber.MaxIdle ... maximum number of idle iterations (default is 200000)
    066     * <li>HillClimber.Neighbours ... semicolon separated list of classes implementing {@link NeighbourSelection}
    067     * <li>HillClimber.AdditionalNeighbours ... semicolon separated list of classes implementing {@link NeighbourSelection}
    068     * <li>HillClimber.Random ... when true, a neighbour selector is selected randomly
    069     * <li>HillClimber.Update ... when true, a neighbour selector is selected using {@link NeighbourSelector#getPoints()} weights (roulette wheel selection)
    070     * </ul>
    071     */
    072    public HillClimber(DataProperties properties) {
    073        super(properties);
    074        iMaxIdleIters = properties.getPropertyInt(getParameterBaseName() + ".MaxIdle", iMaxIdleIters);
    075        iSetHCMode = properties.getPropertyBoolean(getParameterBaseName() + ".SetHCMode", iSetHCMode);
    076    }
    077
    078    /**
    079     * Set progress phase name
    080     */
    081    public void setPhase(String phase) {
    082        iPhase = phase;
    083    }
    084
    085    /**
    086     * Initialization
    087     */
    088    @Override
    089    public void init(Solver<V, T> solver) {
    090        super.init(solver);
    091        if (iSetHCMode)
    092            setHCMode(true);
    093    }
    094
    095    /**
    096     * Increase iteration counter
    097     */
    098    @Override
    099    protected void incIteration(Solution<V, T> solution) {
    100        super.incIteration(solution);
    101        if (iIter % 10000 == 0) {
    102            iLog.info("Iter=" + (iIter / 1000)+"k, NonImpIter=" + iDF2.format((iIter-iLastImprovingIter)/1000.0)+"k, Speed="+iDF2.format(1000.0*iIter/getTimeMillis())+" it/s");
    103            logNeibourStatus();
    104        }
    105        iProgress.setProgress(Math.round(100.0 * (iIter - iLastImprovingIter) / iMaxIdleIters));
    106    }
    107
    108    /**
    109     * Stop the search after a given number of idle (not improving) iterations
    110     */
    111    @Override
    112    protected boolean canContinue(Solution<V, T> solution) {
    113        return iIter - iLastImprovingIter < iMaxIdleIters;
    114    }
    115
    116    /**
    117     * Reset the idle iterations counter
    118     */
    119    @Override
    120    protected void activate(Solution<V, T> solution) {
    121        super.activate(solution);
    122        iLastImprovingIter = iIter;
    123    }
    124
    125    /**
    126     * Memorize the iteration when the last best solution was found.
    127     */
    128    @Override
    129    public void bestSaved(Solution<V, T> solution) {
    130        if (Math.abs(iBestValue - solution.getBestValue()) >= 1.0) {
    131            iLastImprovingIter = iIter;
    132            iBestValue = solution.getBestValue();
    133        }
    134    }
    135
    136    /**
    137     * Accept any move that does not worsen the solution (value <= 0)
    138     */
    139    @Override
    140    protected boolean accept(Model<V, T> model, Neighbour<V, T> neighbour, double value, boolean lazy) {
    141        return value <= 0;
    142    }
    143
    144    /**
    145     * All parameters start with HillClimber base name, e.g., HillClimber.MaxIdle
    146     */
    147    @Override
    148    public String getParameterBaseName() { return "HillClimber"; }
    149}