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Java example source code file (CycleCrossover.java)

This example Java source code file (CycleCrossover.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

abstractlistchromosome, arraylist, chromosome, chromosomepair, crossoverpolicy, cyclecrossover, dimensionmismatchexception, hashset, list, mathillegalargumentexception, suppresswarnings, util

The CycleCrossover.java Java example source code

/*
 * 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.math3.genetics;

import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;

import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.util.LocalizedFormats;

/**
 * Cycle Crossover [CX] builds offspring from <b>ordered chromosomes by identifying cycles
 * between two parent chromosomes. To form the children, the cycles are copied from the
 * respective parents.
 * <p>
 * To form a cycle the following procedure is applied:
 * <ol>
 *   <li>start with the first gene of parent 1
 *   <li>look at the gene at the same position of parent 2
 *   <li>go to the position with the same gene in parent 1
 *   <li>add this gene index to the cycle
 *   <li>repeat the steps 2-5 until we arrive at the starting gene of this cycle
 * </ol>
 * The indices that form a cycle are then used to form the children in alternating order, i.e.
 * in cycle 1, the genes of parent 1 are copied to child 1, while in cycle 2 the genes of parent 1
 * are copied to child 2, and so forth ...
 * </p>
 *
 * Example (zero-start cycle):
 * <pre>
 * p1 = (8 4 7 3 6 2 5 1 9 0)    X   c1 = (8 1 2 3 4 5 6 7 9 0)
 * p2 = (0 1 2 3 4 5 6 7 8 9)    X   c2 = (0 4 7 3 6 2 5 1 8 9)
 *
 * cycle 1: 8 0 9
 * cycle 2: 4 1 7 2 5 6
 * cycle 3: 3
 * </pre>
 *
 * 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://www.rubicite.com/Tutorials/GeneticAlgorithms/CrossoverOperators/CycleCrossoverOperator.aspx">
 * Cycle Crossover Operator</a>
 *
 * @param <T> generic type of the {@link AbstractListChromosome}s for crossover
 * @since 3.1
 */
public class CycleCrossover<T> implements CrossoverPolicy {

    /** If the start index shall be chosen randomly. */
    private final boolean randomStart;

    /**
     * Creates a new {@link CycleCrossover} policy.
     */
    public CycleCrossover() {
        this(false);
    }

    /**
     * Creates a new {@link CycleCrossover} policy using the given {@code randomStart} behavior.
     *
     * @param randomStart whether the start index shall be chosen randomly or be set to 0
     */
    public CycleCrossover(final boolean randomStart) {
        this.randomStart = randomStart;
    }

    /**
     * Returns whether the starting index is chosen randomly or set to zero.
     *
     * @return {@code true} if the starting index is chosen randomly, {@code false} otherwise
     */
    public boolean isRandomStart() {
        return randomStart;
    }

    /**
     * {@inheritDoc}
     *
     * @throws MathIllegalArgumentException if the chromosomes are not an instance of {@link AbstractListChromosome}
     * @throws DimensionMismatchException if the length of the two chromosomes is different
     */
    @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) 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
     */
    protected ChromosomePair mate(final AbstractListChromosome<T> first, final AbstractListChromosome 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: do a crossover copy to simplify the later processing
        final List<T> child1Rep = new ArrayList(second.getRepresentation());
        final List<T> child2Rep = new ArrayList(first.getRepresentation());

        // the set of all visited indices so far
        final Set<Integer> visitedIndices = new HashSet(length);
        // the indices of the current cycle
        final List<Integer> indices = new ArrayList(length);

        // determine the starting index
        int idx = randomStart ? GeneticAlgorithm.getRandomGenerator().nextInt(length) : 0;
        int cycle = 1;

        while (visitedIndices.size() < length) {
            indices.add(idx);

            T item = parent2Rep.get(idx);
            idx = parent1Rep.indexOf(item);

            while (idx != indices.get(0)) {
                // add that index to the cycle indices
                indices.add(idx);
                // get the item in the second parent at that index
                item = parent2Rep.get(idx);
                // get the index of that item in the first parent
                idx = parent1Rep.indexOf(item);
            }

            // for even cycles: swap the child elements on the indices found in this cycle
            if (cycle++ % 2 != 0) {
                for (int i : indices) {
                    T tmp = child1Rep.get(i);
                    child1Rep.set(i, child2Rep.get(i));
                    child2Rep.set(i, tmp);
                }
            }

            visitedIndices.addAll(indices);
            // find next starting index: last one + 1 until we find an unvisited index
            idx = (indices.get(0) + 1) % length;
            while (visitedIndices.contains(idx) && visitedIndices.size() < length) {
                idx++;
                if (idx >= length) {
                    idx = 0;
                }
            }
            indices.clear();
        }

        return new ChromosomePair(first.newFixedLengthChromosome(child1Rep),
                                  second.newFixedLengthChromosome(child2Rep));
    }
}

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