net.sourceforge.cilib.pso.crossover.DiscreteVelocityCrossoverStrategy Maven / Gradle / Ivy

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/**           __  __
 *    _____ _/ /_/ /_    Computational Intelligence Library (CIlib)
 *   / ___/ / / / __ \   (c) CIRG @ UP
 *  / /__/ / / / /_/ /   http://cilib.net
 *  \___/_/_/_/_.___/
 */
package net.sourceforge.cilib.pso.crossover;

import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import net.sourceforge.cilib.controlparameter.ControlParameter;
import net.sourceforge.cilib.entity.Entity;
import net.sourceforge.cilib.entity.EntityType;
import net.sourceforge.cilib.entity.operators.crossover.CrossoverStrategy;
import net.sourceforge.cilib.entity.operators.crossover.DiscreteCrossoverStrategy;
import net.sourceforge.cilib.entity.operators.crossover.OnePointCrossoverStrategy;
import net.sourceforge.cilib.pso.crossover.pbestupdate.CurrentPositionOffspringPBestProvider;
import net.sourceforge.cilib.pso.crossover.pbestupdate.OffspringPBestProvider;
import net.sourceforge.cilib.pso.particle.Particle;
import net.sourceforge.cilib.util.selection.recipes.ElitistSelector;

public class DiscreteVelocityCrossoverStrategy implements CrossoverStrategy {

    private DiscreteCrossoverStrategy crossoverStrategy;
    private OffspringPBestProvider pbestProvider;

    public DiscreteVelocityCrossoverStrategy() {
        this.crossoverStrategy = new OnePointCrossoverStrategy();
        this.pbestProvider = new CurrentPositionOffspringPBestProvider();
    }

    public DiscreteVelocityCrossoverStrategy(DiscreteVelocityCrossoverStrategy copy) {
        this.crossoverStrategy = copy.crossoverStrategy.getClone();
        this.pbestProvider = copy.pbestProvider;
    }

    public CrossoverStrategy getClone() {
        return new DiscreteVelocityCrossoverStrategy(this);
    }

    public  List crossover(List parentCollection) {
        List parents = (List) parentCollection;
        List offspring = crossoverStrategy.crossover(parents);
        List offspringVelocity = new ArrayList();
        Particle nBest = new ElitistSelector().on(parents).select();

        for (Particle p : parents) {
            Particle v = p.getClone();
            v.setCandidateSolution(v.getVelocity());
            offspringVelocity.add(v);
        }

        offspringVelocity = crossoverStrategy.crossover(offspringVelocity, crossoverStrategy.getCrossoverPoints());

        Iterator vIter = offspringVelocity.iterator();
        for (Particle p : offspring) {
            p.getProperties().put(EntityType.Particle.BEST_POSITION, pbestProvider.f(parents, p));

            Particle pbCalc = p.getClone();
            pbCalc.setNeighbourhoodBest(nBest);
            pbCalc.setCandidateSolution(p.getBestPosition());
            pbCalc.calculateFitness();

            p.getProperties().put(EntityType.Particle.BEST_FITNESS, pbCalc.getFitness());
            p.getProperties().put(EntityType.Particle.VELOCITY, vIter.next().getCandidateSolution());

            p.setNeighbourhoodBest(nBest);
            p.calculateFitness();
        }

        return (List) offspring;
    }

    public int getNumberOfParents() {
        return crossoverStrategy.getNumberOfParents();
    }

    public void setCrossoverStrategy(DiscreteCrossoverStrategy crossoverStrategy) {
        this.crossoverStrategy = crossoverStrategy;
    }

    public DiscreteCrossoverStrategy getCrossoverStrategy() {
        return crossoverStrategy;
    }

    public void setPbestProvider(OffspringPBestProvider pbestProvider) {
        this.pbestProvider = pbestProvider;
    }

    public OffspringPBestProvider getPbestProvider() {
        return pbestProvider;
    }

    public void setCrossoverPointProbability(double crossoverPointProbability) {
        throw new UnsupportedOperationException("Not applicable");
    }

    public ControlParameter getCrossoverPointProbability() {
        throw new UnsupportedOperationException("Not applicable");
    }
}