use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.
the class TestBooths method testBoothsFitness.
@Test
public void testBoothsFitness() {
Problem p = new Booths();
FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
double[] values = { -2.0, 1.0 };
NSGAChromosome c = new NSGAChromosome(-10.0, 10.0, 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(f1.getFitness(c), 113.0, 0.0);
double[] values_m = { 1.0, 3.0 };
c = new NSGAChromosome(-10.0, 10.0, values_m);
Assert.assertEquals(f1.getFitness(c), 0.0, 0.0);
}
use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.
the class TestBooths method testBooths.
/**
* Testing NSGA-II with Booths Problem
*
* @throws IOException
* @throws NumberFormatException
*/
@Test
public void testBooths() throws NumberFormatException, IOException {
Properties.MUTATION_RATE = 1d / 2d;
ChromosomeFactory<?> factory = new RandomFactory(false, 2, -10.0, 10.0);
// 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 Booths();
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));
}
}
use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.
the class TestThreeHump method testThreeHumpFitness.
@Test
public void testThreeHumpFitness() {
Problem p = new ThreeHump();
FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
double[] values = { -2.0, 3.0 };
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(), 3.0, 0.0);
Assert.assertEquals(f1.getFitness(c), 4.87, 0.01);
}
use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.
the class TestDominanceComparator method testDominanceComparatorOneFitness.
@Test
public void testDominanceComparatorOneFitness() {
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, 0.7);
c2.setFitness(ff, 0.3);
List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
population.add(c1);
population.add(c2);
DominanceComparator dc = new DominanceComparator();
Collections.sort(population, dc);
Assert.assertEquals(population.get(0).getFitness(ff), 0.3, 0.0);
Assert.assertEquals(population.get(1).getFitness(ff), 0.7, 0.0);
}
use of org.evosuite.ga.problems.Problem in project evosuite by EvoSuite.
the class TestDominanceComparator method testDominanceComparatorSeveralFitnessesDomination.
@Test
public void testDominanceComparatorSeveralFitnessesDomination() {
Problem p = new FON();
List<FitnessFunction<NSGAChromosome>> fitnessFunctions = p.getFitnessFunctions();
FitnessFunction<NSGAChromosome> ff_1 = fitnessFunctions.get(0);
FitnessFunction<NSGAChromosome> ff_2 = fitnessFunctions.get(1);
NSGAChromosome c1 = new NSGAChromosome();
NSGAChromosome c2 = new NSGAChromosome();
// Set Fitness
c1.setFitness(ff_1, 0.7);
c1.setFitness(ff_2, 0.6);
c2.setFitness(ff_1, 0.3);
c2.setFitness(ff_2, 0.5);
List<NSGAChromosome> population = new ArrayList<NSGAChromosome>();
population.add(c1);
population.add(c2);
DominanceComparator dc = new DominanceComparator();
Collections.sort(population, dc);
Assert.assertEquals(population.get(0).getFitness(ff_1), 0.3, 0.0);
Assert.assertEquals(population.get(0).getFitness(ff_2), 0.5, 0.0);
Assert.assertEquals(population.get(1).getFitness(ff_1), 0.7, 0.0);
Assert.assertEquals(population.get(1).getFitness(ff_2), 0.6, 0.0);
}
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