/**
* 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.problems.multiobjective;
import java.util.ArrayList;
import java.util.List;
import org.evosuite.ga.Chromosome;
import org.evosuite.ga.FitnessFunction;
import org.evosuite.ga.NSGAChromosome;
import org.evosuite.ga.problems.Problem;
import org.evosuite.ga.variables.DoubleVariable;
/**
* SCH2 Problem
*
* @author José Campos
*/
@SuppressWarnings({ "rawtypes", "unchecked", "serial" })
public class SCH2<T extends NSGAChromosome> implements Problem
{
private List<FitnessFunction<T>> fitnessFunctions = new ArrayList<FitnessFunction<T>>();
public SCH2() {
super();
/**
* First fitness function
*/
class f1FitnessFunction extends FitnessFunction {
@Override
public double getFitness(Chromosome c) {
NSGAChromosome individual = (NSGAChromosome)c;
double x = ((DoubleVariable) individual.getVariables().get(0)).getValue();
double fitness = 0.0;
if (x <= 1.0)
fitness = -x;
else if (x > 1.0 && x <= 3.0)
fitness = x - 2.0;
else if (x > 3.0 && x <= 4.0)
fitness = 4.0 - x;
else if (x > 4.0)
fitness = x - 4.0;
updateIndividual(this, individual, fitness);
return fitness;
}
@Override
public boolean isMaximizationFunction() {
return false;
}
}
/**
* Second fitness function
*/
class f2FitnessFunction extends FitnessFunction {
@Override
public double getFitness(Chromosome c) {
NSGAChromosome individual = (NSGAChromosome)c;
double x = ((DoubleVariable) individual.getVariables().get(0)).getValue();
double fitness = Math.pow(x - 5.0, 2.0);
updateIndividual(this, individual, fitness);
return fitness;
}
@Override
public boolean isMaximizationFunction() {
return false;
}
}
this.fitnessFunctions.add(new f1FitnessFunction());
this.fitnessFunctions.add(new f2FitnessFunction());
}
@Override
public List<FitnessFunction<T>> getFitnessFunctions() {
return this.fitnessFunctions;
}
}