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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.

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/*
 * 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 ordered chromosomes by identifying cycles
 * between two parent chromosomes. To form the children, the cycles are copied from the
 * respective parents.
 * 

* To form a cycle the following procedure is applied: *

    *
  1. start with the first gene of parent 1
  2. *
  3. look at the gene at the same position of parent 2
  4. *
  5. go to the position with the same gene in parent 1
  6. *
  7. add this gene index to the cycle
  8. *
  9. repeat the steps 2-5 until we arrive at the starting gene of this cycle
  10. *
* 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 ... *

* * Example (zero-start cycle): *
 * 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
 * 
* * This policy works only on {@link AbstractListChromosome}, and therefore it * is parameterized by T. Moreover, the chromosomes must have same lengths. * * @see * Cycle Crossover Operator * * @param generic type of the {@link AbstractListChromosome}s for crossover * @since 3.1 */ public class CycleCrossover 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) 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 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 parent1Rep = first.getRepresentation(); final List parent2Rep = second.getRepresentation(); // and of the children: do a crossover copy to simplify the later processing final List child1Rep = new ArrayList(second.getRepresentation()); final List child2Rep = new ArrayList(first.getRepresentation()); // the set of all visited indices so far final Set visitedIndices = new HashSet(length); // the indices of the current cycle final List 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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