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

import fj.F;
import java.util.Iterator;

import net.sourceforge.cilib.algorithm.population.SinglePopulationBasedAlgorithm;
import net.sourceforge.cilib.entity.Entity;
import net.sourceforge.cilib.entity.EntityType;
import net.sourceforge.cilib.entity.Topologies;
import net.sourceforge.cilib.math.random.generator.Rand;
import net.sourceforge.cilib.pso.dynamic.DynamicParticle;
import net.sourceforge.cilib.pso.particle.Particle;
import net.sourceforge.cilib.type.types.Numeric;
import net.sourceforge.cilib.type.types.container.Vector;
import net.sourceforge.cilib.util.Vectors;


public class PartialReinitialisationResponseStrategy extends ParticleReevaluationResponseStrategy {

    private static final long serialVersionUID = 4619744183683905269L;
    private double reinitialisationRatio;

    public PartialReinitialisationResponseStrategy() {
        super();
        reinitialisationRatio = 0.5;
    }

    public PartialReinitialisationResponseStrategy(PartialReinitialisationResponseStrategy copy) {
        this.reinitialisationRatio = copy.reinitialisationRatio;
    }

    @Override
    public PartialReinitialisationResponseStrategy getClone() {
        return new PartialReinitialisationResponseStrategy(this);
    }

    /**
     * Respond to environment change by re-evaluating each particle's position, personal best and neighbourhood best,
     * and reinitialising the positions of a specified percentage of particles.
     * @param algorithm PSO algorithm that has to respond to environment change
     */
    @Override
	protected 

> void performReaction( A algorithm) { fj.data.List topology = algorithm.getTopology(); // Reevaluate current position. Update personal best (done by reevaluate()). Iterator iterator = topology.iterator(); int reinitCounter = 0; int keepCounter = 0; int populationSize = algorithm.getTopology().length(); while (iterator.hasNext()) { DynamicParticle current = (DynamicParticle) iterator.next(); ZeroTransformation zt = new ZeroTransformation(); //makes sure the charged particles are randomly positioned across the topology if (reinitCounter < Math.floor(populationSize * reinitialisationRatio) && Rand.nextDouble() < reinitialisationRatio && current != Topologies.getBestEntity(algorithm.getTopology())) { current.getPosition().randomise(); current.getProperties().put(EntityType.Particle.VELOCITY, Vectors.transform(current.getVelocity(), zt)); current.getProperties().put(EntityType.Particle.BEST_POSITION, Vector.copyOf(current.getPosition())); ++reinitCounter; }//if else if (keepCounter > Math.floor(populationSize * (1.0 - reinitialisationRatio)) && current != Topologies.getBestEntity(algorithm.getTopology())) { current.getPosition().randomise(); current.getProperties().put(EntityType.Particle.VELOCITY, Vectors.transform(current.getVelocity(), zt)); current.getProperties().put(EntityType.Particle.BEST_POSITION, Vector.copyOf(current.getPosition())); ++reinitCounter; }//else if else { ++keepCounter; }//else } // Re-evaluate: reevaluateParticles(algorithm); // super class method } /** * @return the reinitialisationRatio */ public double getReinitialisationRatio() { return reinitialisationRatio; } /** * @param reinitialisationRatio the reinitialisationRatio to set */ public void setReinitialisationRatio(double reinitialisationRatio) { this.reinitialisationRatio = reinitialisationRatio; } private static class ZeroTransformation extends F { @Override public Number f(Numeric from) { return 0.0; } } }





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