📄 multiobjectivefitnessfunction.java
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/*
* This file is part of JGAP.
*
* JGAP offers a dual license model containing the LGPL as well as the MPL.
*
* For licencing information please see the file license.txt included with JGAP
* or have a look at the top of class org.jgap.Chromosome which representatively
* includes the JGAP license policy applicable for any file delivered with JGAP.
*/
package examples.multiobjective;
import java.util.*;
import org.jgap.*;
import org.jgap.impl.*;
/**
* Sample fitness function for the multiobjective problem.
*
* @author Klaus Meffert
* @since 2.6
*/
public class MultiObjectiveFitnessFunction
extends BulkFitnessFunction {
/** String containing the CVS revision. Read out via reflection!*/
private final static String CVS_REVISION = "$Revision: 1.2 $";
public static final int MAX_BOUND = 4000;
public static final double MIN_X = -10;
public static final double MAX_X = 10;
/**
* Determine the fitness of the given Chromosome instance. The higher the
* returned value, the fitter the instance. This method should always
* return the same fitness value for two equivalent Chromosome instances.
*
* @param a_subject the population of chromosomes to evaluate
*
* @author Klaus Meffert
* @since 2.6
*/
public void evaluate(Population a_subject) {
Iterator it = a_subject.getChromosomes().iterator();
while (it.hasNext()) {
IChromosome a_chrom1 = (IChromosome) it.next();
// evaluate values to fill vector of multiobjectives with
DoubleGene g1 = (DoubleGene) a_chrom1.getGene(0);
double d = g1.doubleValue();
double y1 = formula(1, d);
List l = new Vector();
l.add(new Double(y1));
double y2 = formula(2, d);
l.add(new Double(y2));
( (Chromosome) a_chrom1).setMultiObjectives(l);
}
}
public static Vector getVector(IChromosome a_chrom) {
Vector result = new Vector();
// Gene g1 = a_chrom.getGene(0);
// result.add(g1);
// Gene g2 = a_chrom.getGene(1);
// result.add(g2);
List mo = ( (Chromosome) a_chrom).getMultiObjectives();
Double d = (Double) mo.get(0);
result.add(d);
d = (Double) mo.get(1);
result.add(d);
return result;
}
private double formula(int a_index, double a_x) {
if (a_index == 1) {
return a_x * a_x;
}
else {
return (a_x - 2) * (a_x - 2);
}
}
/**
* @return deep clone of the current instance
*
* @author Klaus Meffert
* @since 3.2
*/
public Object clone() {
return new MultiObjectiveFitnessFunction();
}
}
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