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}