/**
* Copyright (C) 2010-2017 Gordon Fraser, Andrea Arcuri and EvoSuite
* contributors
*
* This file is part of EvoSuite.
*
* EvoSuite is free software: you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License as published
* by the Free Software Foundation, either version 3.0 of the License, or
* (at your option) any later version.
*
* EvoSuite is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with EvoSuite. If not, see <http://www.gnu.org/licenses/>.
*/
package org.evosuite.ga.operators.crossover;
import org.evosuite.ga.Chromosome;
import org.evosuite.ga.ConstructionFailedException;
import org.evosuite.ga.NSGAChromosome;
import org.evosuite.ga.variables.DoubleVariable;
import org.evosuite.ga.variables.Variable;
import org.evosuite.utils.Randomness;
/**
* Simulated Binary Crossover (SBX)
*
* @author José Campos
*/
public class SBXCrossover<T extends NSGAChromosome> extends CrossOverFunction
{
private static final long serialVersionUID = -4258729002155733390L;
/**
* EPS defines the minimum difference allowed between real values
*/
private static final double EPS = 1e-10;
@Override
public void crossOver(Chromosome p1, Chromosome p2)
throws ConstructionFailedException
{
NSGAChromosome n1 = (NSGAChromosome) p1;
NSGAChromosome n2 = (NSGAChromosome) p2;
for (int i = 0; i < n1.getNumberOfVariables(); i++)
{
Variable v1 = n1.getVariable(i);
Variable v2 = n2.getVariable(i);
if ((v1 instanceof DoubleVariable) && (v2 instanceof DoubleVariable))
this.doCrossover((DoubleVariable) v1, (DoubleVariable) v2);
}
}
private void doCrossover(DoubleVariable v1, DoubleVariable v2)
{
double distributionIndex = 20.0;
double rand;
double y1, y2, yL, yu;
double c1, c2;
double alpha, beta, betaq;
double valueX1, valueX2;
yL = v1.getLowerBound();
yu = v1.getUpperBound();
valueX1 = v1.getValue();
valueX2 = v2.getValue();
if (Math.abs(valueX1 - valueX2) > EPS)
{
if (valueX1 < valueX2) {
y1 = valueX1;
y2 = valueX2;
}
else {
y1 = valueX2;
y2 = valueX1;
}
rand = Randomness.nextDouble();
beta = 1.0 + (2.0 * (y1 - yL) / (y2 - y1));
alpha = 2.0 - Math.pow(beta, -(distributionIndex + 1.0));
if (rand <= (1.0 / alpha))
betaq = Math.pow((rand * alpha), (1.0 / (distributionIndex + 1.0)));
else
betaq = Math.pow((1.0 / (2.0 - rand * alpha)), (1.0 / (distributionIndex + 1.0)));
c1 = 0.5 * ((y1 + y2) - betaq * (y2 - y1));
beta = 1.0 + (2.0 * (yu - y2) / (y2 - y1));
alpha = 2.0 - Math.pow(beta, -(distributionIndex + 1.0));
if (rand <= (1.0 / alpha))
betaq = Math.pow((rand * alpha), (1.0 / (distributionIndex + 1.0)));
else
betaq = Math.pow((1.0 / (2.0 - rand * alpha)), (1.0 / (distributionIndex + 1.0)));
c2 = 0.5 * ((y1 + y2) + betaq * (y2 - y1));
if (c1 < yL)
c1 = yL;
if (c2 < yL)
c2 = yL;
if (c1 > yu)
c1 = yu;
if (c2 > yu)
c2 = yu;
if (Randomness.nextDouble() <= 0.5) {
valueX1 = c2;
valueX2 = c1;
}
else {
valueX1 = c1;
valueX2 = c2;
}
v1.setValue(valueX1);
v2.setValue(valueX2);
}
}
}