TournamentSelector.java
package net.bmahe.genetics4j.core.selection;
import java.util.Comparator;
import java.util.List;
import java.util.random.RandomGenerator;
import org.apache.commons.lang3.Validate;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import net.bmahe.genetics4j.core.Genotype;
import net.bmahe.genetics4j.core.Individual;
import net.bmahe.genetics4j.core.Population;
import net.bmahe.genetics4j.core.spec.AbstractEAConfiguration;
import net.bmahe.genetics4j.core.spec.selection.SelectionPolicy;
import net.bmahe.genetics4j.core.spec.selection.Tournament;
public class TournamentSelector<T extends Comparable<T>> implements Selector<T> {
public static final Logger logger = LogManager.getLogger(TournamentSelector.class);
private final SelectionPolicy selectionPolicy;
private final RandomGenerator randomGenerator;
public TournamentSelector(final SelectionPolicy _selectionPolicy, final RandomGenerator _randomGenerator) {
Validate.notNull(_selectionPolicy);
Validate.isInstanceOf(Tournament.class, _selectionPolicy);
Validate.notNull(_randomGenerator);
this.selectionPolicy = _selectionPolicy;
this.randomGenerator = _randomGenerator;
}
@Override
public Population<T> select(final AbstractEAConfiguration<T> eaConfiguration, final int numIndividuals,
final List<Genotype> population, final List<T> fitnessScore) {
Validate.notNull(eaConfiguration);
Validate.notNull(population);
Validate.notNull(fitnessScore);
Validate.isTrue(numIndividuals > 0);
Validate.isTrue(population.size() == fitnessScore.size());
@SuppressWarnings("unchecked")
final Tournament<T> tournamentSelection = (Tournament<T>) selectionPolicy;
final Comparator<Individual<T>> baseComparator = tournamentSelection.comparator();
final Comparator<Individual<T>> comparator = switch (eaConfiguration.optimization()) {
case MAXIMIZE -> baseComparator;
case MINIMIZE -> baseComparator.reversed();
};
logger.debug("Selecting {} individuals", numIndividuals);
final Population<T> selectedIndividuals = new Population<>();
while (selectedIndividuals.size() < numIndividuals) {
Individual<T> bestIndividual = null;
for (int i = 0; i < tournamentSelection.numCandidates(); i++) {
final int candidateIndex = randomGenerator.nextInt(fitnessScore.size());
final Individual<T> candidate = Individual.of(population.get(candidateIndex),
fitnessScore.get(candidateIndex));
if (bestIndividual == null || comparator.compare(bestIndividual, candidate) < 0) {
bestIndividual = candidate;
}
}
selectedIndividuals.add(bestIndividual);
}
return selectedIndividuals;
}
}