use of org.evosuite.ga.FitnessFunction in project evosuite by EvoSuite.
the class KURIntTest method testKURFitnesses.
@Test
public void testKURFitnesses() {
Problem p = new KUR();
FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
double[] values = { -2, 1, 3 };
NSGAChromosome c = new NSGAChromosome(-5.0, 5.0, values);
Assert.assertEquals(((DoubleVariable) c.getVariables().get(0)).getValue(), -2.0, 0.0);
Assert.assertEquals(((DoubleVariable) c.getVariables().get(1)).getValue(), 1.0, 0.0);
Assert.assertEquals(((DoubleVariable) c.getVariables().get(2)).getValue(), 3.0, 0.0);
Assert.assertEquals(f1.getFitness(c), -11.706929282948648, 0.0);
Assert.assertEquals(f2.getFitness(c), 9.191769144818029, 0.0);
}
use of org.evosuite.ga.FitnessFunction in project evosuite by EvoSuite.
the class POLIntTest method testPOL.
/**
* Testing NSGA-II with POL Problem
*
* @throws IOException
* @throws NumberFormatException
*/
@Test
public void testPOL() throws NumberFormatException, IOException {
Properties.MUTATION_RATE = 1d / 2d;
ChromosomeFactory<?> factory = new RandomFactory(false, 2, -Math.PI, Math.PI);
GeneticAlgorithm<?> ga = new NSGAII(factory);
BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
ga.setSelectionFunction(ts);
ga.setCrossOverFunction(new SBXCrossover());
Problem p = new POL();
final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
final FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
ga.addFitnessFunction(f1);
ga.addFitnessFunction(f2);
// execute
ga.generateSolution();
List<Chromosome> chromosomes = (List<Chromosome>) ga.getPopulation();
Collections.sort(chromosomes, new Comparator<Chromosome>() {
@Override
public int compare(Chromosome arg0, Chromosome arg1) {
return Double.compare(arg0.getFitness(f1), arg1.getFitness(f1));
}
});
double[][] front = new double[Properties.POPULATION][2];
int index = 0;
for (Chromosome chromosome : chromosomes) {
System.out.printf("%f,%f\n", chromosome.getFitness(f1), chromosome.getFitness(f2));
front[index][0] = Double.valueOf(chromosome.getFitness(f1));
front[index][1] = Double.valueOf(chromosome.getFitness(f2));
index++;
}
// load True Pareto Front
double[][] trueParetoFront = Metrics.readFront("Poloni.pf");
GenerationalDistance gd = new GenerationalDistance();
double gdd = gd.evaluate(front, trueParetoFront);
System.out.println("GenerationalDistance: " + gdd);
Assert.assertEquals(gdd, 0.0005, 0.0001);
Spacing sp = new Spacing();
double spd = sp.evaluate(front);
double spdt = sp.evaluate(trueParetoFront);
System.out.println("SpacingFront (" + spd + ") - SpacingTrueFront (" + spdt + ") = " + Math.abs(spd - spdt));
Assert.assertEquals(Math.abs(spd - spdt), 0.10, 0.05);
}
use of org.evosuite.ga.FitnessFunction in project evosuite by EvoSuite.
the class POLIntTest method testPOLFitnesses.
@Test
public void testPOLFitnesses() {
Problem p = new POL();
FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
double[] values = { -2.9272124303, 2.7365080818 };
NSGAChromosome c = new NSGAChromosome(-Math.PI, Math.PI, values);
Assert.assertEquals(f1.getFitness(c), 9.25584063461892, 0.0);
Assert.assertEquals(f2.getFitness(c), 13.966790675659546, 0.0);
}
use of org.evosuite.ga.FitnessFunction in project evosuite by EvoSuite.
the class SCHIntTest method testSCH.
/**
* Testing NSGA-II with SCH Problem
*
* @throws IOException
* @throws NumberFormatException
*/
@Test
public void testSCH() throws NumberFormatException, IOException {
Properties.MUTATION_RATE = 1d / 1d;
ChromosomeFactory<?> factory = new RandomFactory(false, 1, Math.pow(-10.0, 3.0), Math.pow(10.0, 3.0));
GeneticAlgorithm<?> ga = new NSGAII(factory);
BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
ts.setMaximize(false);
ga.setSelectionFunction(ts);
ga.setCrossOverFunction(new SBXCrossover());
Problem p = new SCH();
final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
final FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
ga.addFitnessFunction(f1);
ga.addFitnessFunction(f2);
// execute
ga.generateSolution();
List<Chromosome> chromosomes = (List<Chromosome>) ga.getPopulation();
Collections.sort(chromosomes, new Comparator<Chromosome>() {
@Override
public int compare(Chromosome arg0, Chromosome arg1) {
return Double.compare(arg0.getFitness(f1), arg1.getFitness(f1));
}
});
double[][] front = new double[Properties.POPULATION][2];
int index = 0;
for (Chromosome chromosome : chromosomes) {
System.out.printf("%f,%f\n", chromosome.getFitness(f1), chromosome.getFitness(f2));
front[index][0] = Double.valueOf(chromosome.getFitness(f1));
front[index][1] = Double.valueOf(chromosome.getFitness(f2));
index++;
}
// load True Pareto Front
double[][] trueParetoFront = Metrics.readFront("Schaffer.pf");
GenerationalDistance gd = new GenerationalDistance();
double gdd = gd.evaluate(front, trueParetoFront);
System.out.println("GenerationalDistance: " + gdd);
Assert.assertEquals(gdd, 0.0006, 0.0001);
Spacing sp = new Spacing();
double spd = sp.evaluate(front);
double spdt = sp.evaluate(trueParetoFront);
System.out.println("SpacingFront (" + spd + ") - SpacingTrueFront (" + spdt + ") = " + Math.abs(spd - spdt));
Assert.assertEquals(Math.abs(spd - spdt), 1.15, 0.05);
}
use of org.evosuite.ga.FitnessFunction in project evosuite by EvoSuite.
the class ZDT4IntTest method testZDT4.
/**
* Testing NSGA-II with ZDT4 Problem
*
* @throws IOException
* @throws NumberFormatException
*/
@Test
public void testZDT4() throws NumberFormatException, IOException {
Properties.MUTATION_RATE = 1d / 10d;
ChromosomeFactory<?> factory = new RandomFactory(true, 10, -5.0, 5.0);
GeneticAlgorithm<?> ga = new NSGAII(factory);
BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
ts.setMaximize(false);
ga.setSelectionFunction(ts);
ga.setCrossOverFunction(new SBXCrossover());
Problem p = new ZDT4();
final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
final FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
ga.addFitnessFunction(f1);
ga.addFitnessFunction(f2);
// execute
ga.generateSolution();
List<Chromosome> chromosomes = (List<Chromosome>) ga.getPopulation();
Collections.sort(chromosomes, new Comparator<Chromosome>() {
@Override
public int compare(Chromosome arg0, Chromosome arg1) {
return Double.compare(arg0.getFitness(f1), arg1.getFitness(f1));
}
});
double[][] front = new double[Properties.POPULATION][2];
int index = 0;
for (Chromosome chromosome : chromosomes) {
System.out.printf("%f,%f\n", chromosome.getFitness(f1), chromosome.getFitness(f2));
front[index][0] = Double.valueOf(chromosome.getFitness(f1));
front[index][1] = Double.valueOf(chromosome.getFitness(f2));
index++;
}
// load True Pareto Front
double[][] trueParetoFront = Metrics.readFront("ZDT4.pf");
GenerationalDistance gd = new GenerationalDistance();
double gdd = gd.evaluate(front, trueParetoFront);
System.out.println("GenerationalDistance: " + gdd);
Assert.assertEquals(gdd, 0.0006, 0.0001);
Spacing sp = new Spacing();
double spd = sp.evaluate(front);
double spdt = sp.evaluate(trueParetoFront);
System.out.println("SpacingFront (" + spd + ") - SpacingTrueFront (" + spdt + ") = " + Math.abs(spd - spdt));
Assert.assertEquals(Math.abs(spd - spdt), 0.20, 0.10);
}
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