1 package net.bmahe.genetics4j.core.selection;
2
3 import java.util.Comparator;
4 import java.util.List;
5 import java.util.Objects;
6 import java.util.random.RandomGenerator;
7
8 import org.apache.commons.lang3.Validate;
9 import org.apache.logging.log4j.LogManager;
10 import org.apache.logging.log4j.Logger;
11
12 import net.bmahe.genetics4j.core.Genotype;
13 import net.bmahe.genetics4j.core.Individual;
14 import net.bmahe.genetics4j.core.Population;
15 import net.bmahe.genetics4j.core.spec.AbstractEAConfiguration;
16 import net.bmahe.genetics4j.core.spec.selection.SelectionPolicy;
17 import net.bmahe.genetics4j.core.spec.selection.Tournament;
18
19 public class TournamentSelector<T extends Comparable<T>> implements Selector<T> {
20 public static final Logger logger = LogManager.getLogger(TournamentSelector.class);
21
22 private final SelectionPolicy selectionPolicy;
23 private final RandomGenerator randomGenerator;
24
25 public TournamentSelector(final SelectionPolicy _selectionPolicy, final RandomGenerator _randomGenerator) {
26 Objects.requireNonNull(_selectionPolicy);
27 Validate.isInstanceOf(Tournament.class, _selectionPolicy);
28 Objects.requireNonNull(_randomGenerator);
29
30 this.selectionPolicy = _selectionPolicy;
31 this.randomGenerator = _randomGenerator;
32 }
33
34 @Override
35 public Population<T> select(final AbstractEAConfiguration<T> eaConfiguration, final long generation,
36 final int numIndividuals, final List<Genotype> population, final List<T> fitnessScore) {
37 Objects.requireNonNull(eaConfiguration);
38 Objects.requireNonNull(population);
39 Objects.requireNonNull(fitnessScore);
40 Validate.isTrue(generation >= 0);
41 Validate.isTrue(numIndividuals > 0);
42 Validate.isTrue(population.size() == fitnessScore.size());
43
44 @SuppressWarnings("unchecked")
45 final Tournament<T> tournamentSelection = (Tournament<T>) selectionPolicy;
46
47 final Comparator<Individual<T>> baseComparator = tournamentSelection.comparator();
48 final Comparator<Individual<T>> comparator = switch (eaConfiguration.optimization()) {
49 case MAXIMIZE -> baseComparator;
50 case MINIMIZE -> baseComparator.reversed();
51 };
52
53 logger.debug("Selecting {} individuals", numIndividuals);
54
55 final Population<T> selectedIndividuals = new Population<>();
56 while (selectedIndividuals.size() < numIndividuals) {
57
58 Individual<T> bestIndividual = null;
59
60 for (int i = 0; i < tournamentSelection.numCandidates(); i++) {
61 final int candidateIndex = randomGenerator.nextInt(fitnessScore.size());
62 final Individual<T> candidate = Individual.of(population.get(candidateIndex),
63 fitnessScore.get(candidateIndex));
64
65 if (bestIndividual == null || comparator.compare(bestIndividual, candidate) < 0) {
66 bestIndividual = candidate;
67 }
68 }
69
70 selectedIndividuals.add(bestIndividual);
71 }
72
73 return selectedIndividuals;
74 }
75 }