Examples with BinaryTournamentSelectionCrowdedComparison org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison used on opensource projects

Example 11 with BinaryTournamentSelectionCrowdedComparison

use of org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison in project evosuite by EvoSuite.

the class ZDT1IntTest method testZDT1.

/**
 * Testing NSGA-II with ZDT1 Problem
 *
 * @throws IOException
 * @throws NumberFormatException
 */
@Test
public void testZDT1() throws NumberFormatException, IOException {
    Properties.MUTATION_RATE = 1d / 30d;
    ChromosomeFactory<?> factory = new RandomFactory(false, 30, 0.0, 1.0);
    GeneticAlgorithm<?> ga = new NSGAII(factory);
    BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
    ts.setMaximize(false);
    ga.setSelectionFunction(ts);
    ga.setCrossOverFunction(new SBXCrossover());
    Problem p = new ZDT1();
    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("ZDT1.pf");
    GenerationalDistance gd = new GenerationalDistance();
    double gdd = gd.evaluate(front, trueParetoFront);
    System.out.println("GenerationalDistance: " + gdd);
    Assert.assertEquals(gdd, 0.001, 0.001);
    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, 0.10);
}

Example 12 with BinaryTournamentSelectionCrowdedComparison

use of org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison in project evosuite by EvoSuite.

the class TestBeales method testBeales.

/**
 * Testing NSGA-II with Beales Problem
 *
 * @throws IOException
 * @throws NumberFormatException
 */
@Test
public void testBeales() throws NumberFormatException, IOException {
    Properties.MUTATION_RATE = 1d / 2d;
    ChromosomeFactory<?> factory = new RandomFactory(false, 2, -4.5, 4.5);
    // GeneticAlgorithm<?> ga = new NSGAII(factory);
    GeneticAlgorithm<?> ga = new NSGAII(factory);
    BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
    // BinaryTournament ts = new BinaryTournament();
    ga.setSelectionFunction(ts);
    ga.setCrossOverFunction(new SBXCrossover());
    Problem p = new Beales();
    final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
    ga.addFitnessFunction(f1);
    // 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));
        }
    });
    for (Chromosome chromosome : chromosomes) Assert.assertEquals(chromosome.getFitness(f1), 0.29, 0.01);
    for (Chromosome chromosome : chromosomes) {
        NSGAChromosome nsga_c = (NSGAChromosome) chromosome;
        DoubleVariable x = (DoubleVariable) nsga_c.getVariables().get(0);
        DoubleVariable y = (DoubleVariable) nsga_c.getVariables().get(1);
        System.out.printf("%f,%f : %f\n", x.getValue(), y.getValue(), chromosome.getFitness(f1));
    }
}

Example 13 with BinaryTournamentSelectionCrowdedComparison

use of org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison in project evosuite by EvoSuite.

the class TestShere method testSphere.

/**
 * Testing NSGA-II with Sphere Problem
 *
 * @throws IOException
 * @throws NumberFormatException
 */
@Test
public void testSphere() 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);
    GeneticAlgorithm<?> ga = new NSGAII(factory);
    BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
    // BinaryTournament ts = new BinaryTournament();
    ga.setSelectionFunction(ts);
    ga.setCrossOverFunction(new SBXCrossover());
    Problem p = new Sphere();
    final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
    ga.addFitnessFunction(f1);
    // 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));
        }
    });
    for (Chromosome chromosome : chromosomes) Assert.assertEquals(chromosome.getFitness(f1), 0.00, 0.01);
    for (Chromosome chromosome : chromosomes) {
        NSGAChromosome nsga_c = (NSGAChromosome) chromosome;
        DoubleVariable x = (DoubleVariable) nsga_c.getVariables().get(0);
        System.out.printf("%f : %f\n", x.getValue(), chromosome.getFitness(f1));
    }
}