001/*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements.  See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License.  You may obtain a copy of the License at
008 *
009 *      http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017package org.apache.commons.math3.genetics;
018
019import java.util.ArrayList;
020import java.util.Collections;
021import java.util.HashSet;
022import java.util.List;
023import java.util.Set;
024
025import org.apache.commons.math3.exception.DimensionMismatchException;
026import org.apache.commons.math3.exception.MathIllegalArgumentException;
027import org.apache.commons.math3.exception.util.LocalizedFormats;
028import org.apache.commons.math3.random.RandomGenerator;
029import org.apache.commons.math3.util.FastMath;
030
031/**
032 * Order 1 Crossover [OX1] builds offspring from <b>ordered</b> chromosomes by copying a
033 * consecutive slice from one parent, and filling up the remaining genes from the other
034 * parent as they appear.
035 * <p>
036 * This policy works by applying the following rules:
037 * <ol>
038 *   <li>select a random slice of consecutive genes from parent 1</li>
039 *   <li>copy the slice to child 1 and mark out the genes in parent 2</li>
040 *   <li>starting from the right side of the slice, copy genes from parent 2 as they
041 *       appear to child 1 if they are not yet marked out.</li>
042 * </ol>
043 * <p>
044 * Example (random sublist from index 3 to 7, underlined):
045 * <pre>
046 * p1 = (8 4 7 3 6 2 5 1 9 0)   X   c1 = (0 4 7 3 6 2 5 1 8 9)
047 *             ---------                        ---------
048 * p2 = (0 1 2 3 4 5 6 7 8 9)   X   c2 = (8 1 2 3 4 5 6 7 9 0)
049 * </pre>
050 * <p>
051 * This policy works only on {@link AbstractListChromosome}, and therefore it
052 * is parameterized by T. Moreover, the chromosomes must have same lengths.
053 *
054 * @see <a href="http://www.rubicite.com/Tutorials/GeneticAlgorithms/CrossoverOperators/Order1CrossoverOperator.aspx">
055 * Order 1 Crossover Operator</a>
056 *
057 * @param <T> generic type of the {@link AbstractListChromosome}s for crossover
058 * @since 3.1
059 */
060public class OrderedCrossover<T> implements CrossoverPolicy {
061
062    /**
063     * {@inheritDoc}
064     *
065     * @throws MathIllegalArgumentException iff one of the chromosomes is
066     *   not an instance of {@link AbstractListChromosome}
067     * @throws DimensionMismatchException if the length of the two chromosomes is different
068     */
069    @SuppressWarnings("unchecked")
070    public ChromosomePair crossover(final Chromosome first, final Chromosome second)
071        throws DimensionMismatchException, MathIllegalArgumentException {
072
073        if (!(first instanceof AbstractListChromosome<?> && second instanceof AbstractListChromosome<?>)) {
074            throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
075        }
076        return mate((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second);
077    }
078
079    /**
080     * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
081     *
082     * @param first the first chromosome
083     * @param second the second chromosome
084     * @return the pair of new chromosomes that resulted from the crossover
085     * @throws DimensionMismatchException if the length of the two chromosomes is different
086     */
087    protected ChromosomePair mate(final AbstractListChromosome<T> first, final AbstractListChromosome<T> second)
088        throws DimensionMismatchException {
089
090        final int length = first.getLength();
091        if (length != second.getLength()) {
092            throw new DimensionMismatchException(second.getLength(), length);
093        }
094
095        // array representations of the parents
096        final List<T> parent1Rep = first.getRepresentation();
097        final List<T> parent2Rep = second.getRepresentation();
098        // and of the children
099        final List<T> child1 = new ArrayList<T>(length);
100        final List<T> child2 = new ArrayList<T>(length);
101        // sets of already inserted items for quick access
102        final Set<T> child1Set = new HashSet<T>(length);
103        final Set<T> child2Set = new HashSet<T>(length);
104
105        final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
106        // choose random points, making sure that lb < ub.
107        int a = random.nextInt(length);
108        int b;
109        do {
110            b = random.nextInt(length);
111        } while (a == b);
112        // determine the lower and upper bounds
113        final int lb = FastMath.min(a, b);
114        final int ub = FastMath.max(a, b);
115
116        // add the subLists that are between lb and ub
117        child1.addAll(parent1Rep.subList(lb, ub + 1));
118        child1Set.addAll(child1);
119        child2.addAll(parent2Rep.subList(lb, ub + 1));
120        child2Set.addAll(child2);
121
122        // iterate over every item in the parents
123        for (int i = 1; i <= length; i++) {
124            final int idx = (ub + i) % length;
125
126            // retrieve the current item in each parent
127            final T item1 = parent1Rep.get(idx);
128            final T item2 = parent2Rep.get(idx);
129
130            // if the first child already contains the item in the second parent add it
131            if (!child1Set.contains(item2)) {
132                child1.add(item2);
133                child1Set.add(item2);
134            }
135
136            // if the second child already contains the item in the first parent add it
137            if (!child2Set.contains(item1)) {
138                child2.add(item1);
139                child2Set.add(item1);
140            }
141        }
142
143        // rotate so that the original slice is in the same place as in the parents.
144        Collections.rotate(child1, lb);
145        Collections.rotate(child2, lb);
146
147        return new ChromosomePair(first.newFixedLengthChromosome(child1),
148                                  second.newFixedLengthChromosome(child2));
149    }
150}