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     */
017    package org.apache.commons.math3.genetics;
018    
019    import java.util.ArrayList;
020    import java.util.Collections;
021    import java.util.HashSet;
022    import java.util.List;
023    import java.util.Set;
024    
025    import org.apache.commons.math3.exception.DimensionMismatchException;
026    import org.apache.commons.math3.exception.MathIllegalArgumentException;
027    import org.apache.commons.math3.exception.util.LocalizedFormats;
028    import org.apache.commons.math3.random.RandomGenerator;
029    import 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     * @version $Id: OrderedCrossover.java 1385297 2012-09-16 16:05:57Z tn $
060     */
061    public class OrderedCrossover<T> implements CrossoverPolicy {
062    
063        /**
064         * {@inheritDoc}
065         *
066         * @throws MathIllegalArgumentException iff one of the chromosomes is
067         *   not an instance of {@link AbstractListChromosome}
068         * @throws DimensionMismatchException if the length of the two chromosomes is different
069         */
070        @SuppressWarnings("unchecked")
071        public ChromosomePair crossover(final Chromosome first, final Chromosome second)
072            throws DimensionMismatchException, MathIllegalArgumentException {
073    
074            if (!(first instanceof AbstractListChromosome<?> && second instanceof AbstractListChromosome<?>)) {
075                throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
076            }
077            return mate((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second);
078        }
079    
080        /**
081         * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
082         *
083         * @param first the first chromosome
084         * @param second the second chromosome
085         * @return the pair of new chromosomes that resulted from the crossover
086         * @throws DimensionMismatchException if the length of the two chromosomes is different
087         */
088        protected ChromosomePair mate(final AbstractListChromosome<T> first, final AbstractListChromosome<T> second)
089            throws DimensionMismatchException {
090    
091            final int length = first.getLength();
092            if (length != second.getLength()) {
093                throw new DimensionMismatchException(second.getLength(), length);
094            }
095    
096            // array representations of the parents
097            final List<T> parent1Rep = first.getRepresentation();
098            final List<T> parent2Rep = second.getRepresentation();
099            // and of the children
100            final List<T> child1 = new ArrayList<T>(length);
101            final List<T> child2 = new ArrayList<T>(length);
102            // sets of already inserted items for quick access
103            final Set<T> child1Set = new HashSet<T>(length);
104            final Set<T> child2Set = new HashSet<T>(length);
105    
106            final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
107            // choose random points, making sure that lb < ub.
108            int a = random.nextInt(length);
109            int b;
110            do {
111                b = random.nextInt(length);
112            } while (a == b);
113            // determine the lower and upper bounds
114            final int lb = FastMath.min(a, b);
115            final int ub = FastMath.max(a, b);
116    
117            // add the subLists that are between lb and ub
118            child1.addAll(parent1Rep.subList(lb, ub + 1));
119            child1Set.addAll(child1);
120            child2.addAll(parent2Rep.subList(lb, ub + 1));
121            child2Set.addAll(child2);
122    
123            // iterate over every item in the parents
124            for (int i = 1; i <= length; i++) {
125                final int idx = (ub + i) % length;
126    
127                // retrieve the current item in each parent
128                final T item1 = parent1Rep.get(idx);
129                final T item2 = parent2Rep.get(idx);
130    
131                // if the first child already contains the item in the second parent add it
132                if (!child1Set.contains(item2)) {
133                    child1.add(item2);
134                    child1Set.add(item2);
135                }
136    
137                // if the second child already contains the item in the first parent add it
138                if (!child2Set.contains(item1)) {
139                    child2.add(item1);
140                    child2Set.add(item1);
141                }
142            }
143    
144            // rotate so that the original slice is in the same place as in the parents.
145            Collections.rotate(child1, lb);
146            Collections.rotate(child2, lb);
147    
148            return new ChromosomePair(first.newFixedLengthChromosome(child1),
149                                      second.newFixedLengthChromosome(child2));
150        }
151    }