UniformCrossover.java
- /*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements. See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
- package org.apache.commons.math4.legacy.genetics;
- import java.util.ArrayList;
- import java.util.List;
- import org.apache.commons.math4.legacy.exception.DimensionMismatchException;
- import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
- import org.apache.commons.math4.legacy.exception.OutOfRangeException;
- import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
- import org.apache.commons.rng.UniformRandomProvider;
- /**
- * Perform Uniform Crossover [UX] on the specified chromosomes. A fixed mixing
- * ratio is used to combine genes from the first and second parents, e.g. using a
- * ratio of 0.5 would result in approximately 50% of genes coming from each
- * parent. This is typically a poor method of crossover, but empirical evidence
- * suggests that it is more exploratory and results in a larger part of the
- * problem space being searched.
- * <p>
- * This crossover policy evaluates each gene of the parent chromosomes by choosing a
- * uniform random number {@code p} in the range [0, 1]. If {@code p} < {@code ratio},
- * the parent genes are swapped. This means with a ratio of 0.7, 30% of the genes from the
- * first parent and 70% from the second parent will be selected for the first offspring (and
- * vice versa for the second offspring).
- * <p>
- * This policy works only on {@link AbstractListChromosome}, and therefore it
- * is parameterized by T. Moreover, the chromosomes must have same lengths.
- *
- * @see <a href="http://en.wikipedia.org/wiki/Crossover_%28genetic_algorithm%29">Crossover techniques (Wikipedia)</a>
- * @see <a href="http://www.obitko.com/tutorials/genetic-algorithms/crossover-mutation.php">Crossover (Obitko.com)</a>
- * @see <a href="http://www.tomaszgwiazda.com/uniformX.htm">Uniform crossover</a>
- * @param <T> generic type of the {@link AbstractListChromosome}s for crossover
- * @since 3.1
- */
- public class UniformCrossover<T> implements CrossoverPolicy {
- /** The mixing ratio. */
- private final double ratio;
- /**
- * Creates a new {@link UniformCrossover} policy using the given mixing ratio.
- *
- * @param ratio the mixing ratio
- * @throws OutOfRangeException if the mixing ratio is outside the [0, 1] range
- */
- public UniformCrossover(final double ratio) throws OutOfRangeException {
- if (ratio < 0.0d || ratio > 1.0d) {
- throw new OutOfRangeException(LocalizedFormats.CROSSOVER_RATE, ratio, 0.0d, 1.0d);
- }
- this.ratio = ratio;
- }
- /**
- * Returns the mixing ratio used by this {@link CrossoverPolicy}.
- *
- * @return the mixing ratio
- */
- public double getRatio() {
- return ratio;
- }
- /**
- * {@inheritDoc}
- *
- * @throws MathIllegalArgumentException iff one of the chromosomes is
- * not an instance of {@link AbstractListChromosome}
- * @throws DimensionMismatchException if the length of the two chromosomes is different
- */
- @Override
- @SuppressWarnings("unchecked")
- public ChromosomePair crossover(final Chromosome first, final Chromosome second)
- throws DimensionMismatchException, MathIllegalArgumentException {
- if (!(first instanceof AbstractListChromosome<?> && second instanceof AbstractListChromosome<?>)) {
- throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
- }
- return mate((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second);
- }
- /**
- * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
- *
- * @param first the first chromosome
- * @param second the second chromosome
- * @return the pair of new chromosomes that resulted from the crossover
- * @throws DimensionMismatchException if the length of the two chromosomes is different
- */
- private ChromosomePair mate(final AbstractListChromosome<T> first,
- final AbstractListChromosome<T> second) throws DimensionMismatchException {
- final int length = first.getLength();
- if (length != second.getLength()) {
- throw new DimensionMismatchException(second.getLength(), length);
- }
- // array representations of the parents
- final List<T> parent1Rep = first.getRepresentation();
- final List<T> parent2Rep = second.getRepresentation();
- // and of the children
- final List<T> child1Rep = new ArrayList<>(length);
- final List<T> child2Rep = new ArrayList<>(length);
- final UniformRandomProvider random = GeneticAlgorithm.getRandomGenerator();
- for (int index = 0; index < length; index++) {
- if (random.nextDouble() < ratio) {
- // swap the bits -> take other parent
- child1Rep.add(parent2Rep.get(index));
- child2Rep.add(parent1Rep.get(index));
- } else {
- child1Rep.add(parent1Rep.get(index));
- child2Rep.add(parent2Rep.get(index));
- }
- }
- return new ChromosomePair(first.newFixedLengthChromosome(child1Rep),
- second.newFixedLengthChromosome(child2Rep));
- }
- }