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/**
* Description: The description of differential evolution Generate-and-Test Behavior.
#Supported parameters:
NAME VALUE_type Range DefaultV Description
FACTOR real (0, 1.2] 0.5 DEAgent: scale constant
CR real [0, 1] 0.9 DEAgent: crossover constant
//Other choices for FACTOR and CR: (0.5, 0.1)
*
* Author Create/Modi Note
* Xiaofeng Xie May 11, 2004
* Xiaofeng Xie Jul 01, 2008
*
* @version 1.0
* @Since MAOS1.0
*
* @References:
* [1] Storn R, Price K. Differential evolution - a simple and efficient
* heuristic for global optimization over continuous spaces. Journal of
* Global Optimization, 1997, 11: 341-359
* The original differential evolution idea
* [2] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
* optimization. Genetic and Evolutionary Computation Conference (GECCO),
* Seattle, WA, USA, 2004: 238-250
* -> a generate-and-test behavior
*/
package net.adaptivebox.deps.behavior;
import net.adaptivebox.goodness.*;
import net.adaptivebox.global.*;
import net.adaptivebox.knowledge.*;
import net.adaptivebox.problem.*;
import net.adaptivebox.space.*;
public class DEGTBehavior extends AbsGTBehavior implements ILibEngine {
private int DVNum = 2; //Number of differential vectors, normally be 1 or 2
public double FACTOR = 0.5; //scale constant: (0, 1.2], normally be 0.5
public double CR = 0.9; //crossover constant: [0, 1], normally be 0.1 or 0.9
//the own memory: store the point that generated in last learning cycle
private SearchPoint pbest_t;
public void setPbest(SearchPoint pbest) {
pbest_t = pbest;
}
@Override
public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
SearchPoint gbest_t = socialLib.getGbest();
BasicPoint[] referPoints = getReferPoints();
int DIMENSION = problemEncoder.getDesignSpace().getDimension();
int rj = RandomGenerator.intRangeRandom(0, DIMENSION-1);
for (int k=0; k<DIMENSION; k++) {
if (Math.random()<CR || k == DIMENSION-1) {
double Dabcd = 0;
for(int i=0; i<referPoints.length; i++) {
Dabcd += Math.pow(-1, i%2)*referPoints[i].getLocation()[rj];
}
trailPoint.getLocation()[rj] = gbest_t.getLocation()[rj]+FACTOR*Dabcd;
} else {
trailPoint.getLocation()[rj] = pbest_t.getLocation()[rj];
}
rj = (rj+1)%DIMENSION;
}
}
@Override
public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
Library.replace(qualityComparator, trailPoint, pbest_t);
}
private SearchPoint[] getReferPoints() {
SearchPoint[] referPoints = new SearchPoint[DVNum*2];
for(int i=0; i<referPoints.length; i++) {
referPoints[i] = socialLib.getSelectedPoint(RandomGenerator.intRangeRandom(0, socialLib.getPopSize()-1));
}
return referPoints;
}
}
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