1 package net.bmahe.genetics4j.core.selection;
2
3 import java.util.Comparator;
4 import java.util.List;
5 import java.util.random.RandomGenerator;
6
7 import org.apache.commons.lang3.Validate;
8 import org.apache.logging.log4j.LogManager;
9 import org.apache.logging.log4j.Logger;
10
11 import net.bmahe.genetics4j.core.Genotype;
12 import net.bmahe.genetics4j.core.Individual;
13 import net.bmahe.genetics4j.core.Population;
14 import net.bmahe.genetics4j.core.spec.AbstractEAConfiguration;
15 import net.bmahe.genetics4j.core.spec.selection.SelectionPolicy;
16 import net.bmahe.genetics4j.core.spec.selection.Tournament;
17
18 public class TournamentSelector<T extends Comparable<T>> implements Selector<T> {
19 public static final Logger logger = LogManager.getLogger(TournamentSelector.class);
20
21 private final SelectionPolicy selectionPolicy;
22 private final RandomGenerator randomGenerator;
23
24 public TournamentSelector(final SelectionPolicy _selectionPolicy, final RandomGenerator _randomGenerator) {
25 Validate.notNull(_selectionPolicy);
26 Validate.isInstanceOf(Tournament.class, _selectionPolicy);
27 Validate.notNull(_randomGenerator);
28
29 this.selectionPolicy = _selectionPolicy;
30 this.randomGenerator = _randomGenerator;
31 }
32
33 @Override
34 public Population<T> select(final AbstractEAConfiguration<T> eaConfiguration, final int numIndividuals,
35 final List<Genotype> population, final List<T> fitnessScore) {
36 Validate.notNull(eaConfiguration);
37 Validate.notNull(population);
38 Validate.notNull(fitnessScore);
39 Validate.isTrue(numIndividuals > 0);
40 Validate.isTrue(population.size() == fitnessScore.size());
41
42 @SuppressWarnings("unchecked")
43 final Tournament<T> tournamentSelection = (Tournament<T>) selectionPolicy;
44
45 final Comparator<Individual<T>> baseComparator = tournamentSelection.comparator();
46 final Comparator<Individual<T>> comparator = switch (eaConfiguration.optimization()) {
47 case MAXIMIZE -> baseComparator;
48 case MINIMIZE -> baseComparator.reversed();
49 };
50
51 logger.debug("Selecting {} individuals", numIndividuals);
52
53 final Population<T> selectedIndividuals = new Population<>();
54 while (selectedIndividuals.size() < numIndividuals) {
55
56 Individual<T> bestIndividual = null;
57
58 for (int i = 0; i < tournamentSelection.numCandidates(); i++) {
59 final int candidateIndex = randomGenerator.nextInt(fitnessScore.size());
60 final Individual<T> candidate = Individual.of(population.get(candidateIndex),
61 fitnessScore.get(candidateIndex));
62
63 if (bestIndividual == null || comparator.compare(bestIndividual, candidate) < 0) {
64 bestIndividual = candidate;
65 }
66 }
67
68 selectedIndividuals.add(bestIndividual);
69 }
70
71 return selectedIndividuals;
72 }
73 }