Examples with Problem org.evosuite.ga.problems.Problem used on opensource projects

Example 21 with Problem

use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.

the class NSGAIISystemTest method testCrowingDistanceAssignment_OneVariable.

@Test
public void testCrowingDistanceAssignment_OneVariable() {
    NSGAII<NSGAChromosome> ga = new NSGAII<NSGAChromosome>(null);
    Problem p = new Booths();
    List<FitnessFunction<NSGAChromosome>> fitnessFunctions = p.getFitnessFunctions();
    ga.addFitnessFunctions(fitnessFunctions);
    NSGAChromosome c1 = new NSGAChromosome();
    NSGAChromosome c2 = new NSGAChromosome();
    NSGAChromosome c3 = new NSGAChromosome();
    NSGAChromosome c4 = new NSGAChromosome();
    NSGAChromosome c5 = new NSGAChromosome();
    NSGAChromosome c6 = new NSGAChromosome();
    NSGAChromosome c7 = new NSGAChromosome();
    NSGAChromosome c8 = new NSGAChromosome();
    NSGAChromosome c9 = new NSGAChromosome();
    NSGAChromosome c10 = new NSGAChromosome();
    // Set Fitness
    c1.setFitness(fitnessFunctions.get(0), 0.0);
    c2.setFitness(fitnessFunctions.get(0), 0.2);
    c3.setFitness(fitnessFunctions.get(0), 0.4);
    c4.setFitness(fitnessFunctions.get(0), 0.6);
    c5.setFitness(fitnessFunctions.get(0), 0.8);
    c6.setFitness(fitnessFunctions.get(0), 0.0);
    c7.setFitness(fitnessFunctions.get(0), 0.2);
    c8.setFitness(fitnessFunctions.get(0), 0.4);
    c9.setFitness(fitnessFunctions.get(0), 0.6);
    c10.setFitness(fitnessFunctions.get(0), 0.8);
    List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
    population.add(c1);
    population.add(c2);
    population.add(c3);
    population.add(c4);
    population.add(c5);
    population.add(c6);
    population.add(c7);
    population.add(c8);
    population.add(c9);
    population.add(c10);
    ga.crowingDistanceAssignment(population);
    Collections.sort(population, new CrowdingComparator(true));
    Assert.assertTrue(population.get(0).getDistance() == Double.POSITIVE_INFINITY);
    Assert.assertTrue(population.get(1).getDistance() == Double.POSITIVE_INFINITY);
    double epsilon = 1e-10;
    Assert.assertTrue(Math.abs(0.25 - population.get(2).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(3).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(4).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(5).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(6).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(7).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(8).getDistance()) < epsilon);
    Assert.assertTrue(Math.abs(0.25 - population.get(9).getDistance()) < epsilon);
}

Example 22 with Problem

use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.

the class SPEA2Test method testZDT4.

@SuppressWarnings({ "rawtypes", "unchecked" })
@Test
public void testZDT4() throws IOException {
    Properties.MUTATION_RATE = 1d / 10d;
    Properties.POPULATION = 100;
    Properties.SEARCH_BUDGET = 250;
    Properties.STOPPING_CONDITION = StoppingCondition.MAXGENERATIONS;
    Properties.CROSSOVER_RATE = 0.9;
    Properties.RANDOM_SEED = 1l;
    ChromosomeFactory<?> factory = new RandomFactory(true, 10, -5.0, 5.0);
    GeneticAlgorithm<?> ga = new SPEA2(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];
    for (int i = 0; i < chromosomes.size(); i++) {
        Chromosome chromosome = chromosomes.get(i);
        System.out.printf("%f,%f\n", chromosome.getFitness(f1), chromosome.getFitness(f2));
        front[i][0] = Double.valueOf(chromosome.getFitness(f1));
        front[i][1] = Double.valueOf(chromosome.getFitness(f2));
    }
    // 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);
    assertEquals(0.00, gdd, 0.01);
    Spacing sp = new Spacing();
    double spd = sp.evaluate(front);
    System.out.println("SpacingFront: " + spd);
    assertEquals(0.71, spd, 0.01);
}

Example 23 with Problem

use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.

the class SCH2IntTest method testSCH2.

/**
 * Testing NSGA-II with SCH2 Problem
 *
 * @throws IOException
 * @throws NumberFormatException
 */
@Test
public void testSCH2() throws NumberFormatException, IOException {
    Properties.MUTATION_RATE = 1d / 1d;
    ChromosomeFactory<?> factory = new RandomFactory(false, 1, -5.0, 10.0);
    GeneticAlgorithm<?> ga = new NSGAII(factory);
    BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
    ts.setMaximize(false);
    ga.setSelectionFunction(ts);
    ga.setCrossOverFunction(new SBXCrossover());
    Problem p = new SCH2();
    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("Schaffer2.pf");
    GenerationalDistance gd = new GenerationalDistance();
    double gdd = gd.evaluate(front, trueParetoFront);
    System.out.println("GenerationalDistance: " + gdd);
    Assert.assertEquals(gdd, 0.0004, 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), 0.05, 0.05);
}

Example 24 with Problem

use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.

the class TestThreeHump method testThreeHump.

/**
 * Testing NSGA-II with ThreeHump Problem
 *
 * @throws IOException
 * @throws NumberFormatException
 */
@Test
public void testThreeHump() throws NumberFormatException, IOException {
    Properties.MUTATION_RATE = 1d / 2d;
    ChromosomeFactory<?> factory = new RandomFactory(false, 2, -5.0, 5.0);
    // 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 ThreeHump();
    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), 0.000, 0.001);
    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 25 with Problem

use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.

the class TestSortByFitness method testSortByFitnessC2win.

@Test
public void testSortByFitnessC2win() {
    Problem p = new Booths<NSGAChromosome>();
    List<FitnessFunction<NSGAChromosome>> fitnessFunctions = p.getFitnessFunctions();
    FitnessFunction<NSGAChromosome> ff = fitnessFunctions.get(0);
    NSGAChromosome c1 = new NSGAChromosome();
    NSGAChromosome c2 = new NSGAChromosome();
    // Set Fitness
    c1.setFitness(ff, 0.3);
    c2.setFitness(ff, 0.7);
    List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
    population.add(c1);
    population.add(c2);
    SortByFitness sf = new SortByFitness(ff, true);
    Collections.sort(population, sf);
    Assert.assertTrue(population.get(0) == c2);
    Assert.assertEquals(population.get(0).getFitness(ff), 0.7, 0.0);
    Assert.assertEquals(population.get(1).getFitness(ff), 0.3, 0.0);
    Assert.assertTrue(population.get(1) == c1);
}