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source: trunk/sources/HeuristicLab.Encodings.PermutationEncoding/3.3/Crossovers/MaximalPreservativeCrossover.cs @ 3053

Last change on this file since 3053 was 3053, checked in by swagner, 15 years ago

Renamed solution encoding plugins (#909)

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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using HeuristicLab.Core;
24using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
25
26namespace HeuristicLab.Encodings.PermutationEncoding {
27  /// <summary>An operator which performs the maximal preservative crossover on two permutations.</summary>
28  /// <remarks>
29  /// Performs a crossover between two permuation arrays by preserving a large number of edges in both parents.
30  /// The operator also maintains the position in the arrays to some extent.
31  /// It is implemented as described in Mühlenbein, H. 1991. Evolution in time and space - the parallel genetic algorithm. FOUNDATIONS OF GENETIC ALGORITHMS, pp. 316-337. Morgan Kaufmann.<br /><br />
32  /// The length of the segment copied from the first parent to the offspring is uniformly distributed in the interval [3;N/3) with N = length of the permutation.
33  /// This recommendation is mentioned in Pohlheim, H. 1999. Evolutionäre Algorithmen: Verfahren, Operatoren und Hinweise für die Praxis, p. 44, Springer.
34  /// If the length of the permutation is smaller than 15, the size of the segment is always equal to 3.
35  /// </remarks>
36  [Item("MaximalPreservativeCrossover", "An operator which performs the maximal preservative crossover on two permutations. It is implemented as described in Mühlenbein, H. 1991. Evolution in time and space - the parallel genetic algorithm. FOUNDATIONS OF GENETIC ALGORITHMS, pp. 316-337. Morgan Kaufmann.")]
37  [StorableClass]
38  [Creatable("Test")]
39  public class MaximalPreservativeCrossover : PermutationCrossover {
40    /// <summary>
41    /// Performs the maximal preservative crossover on <paramref name="parent1"/> and <paramref name="parent2"/>
42    /// by preserving a large number of edges in both parents.
43    /// </summary>
44    /// <exception cref="ArgumentException">Thrown when <paramref name="parent1"/> and <paramref name="parent2"/> are not of equal length or when the permutations are shorter than 4 elements.</exception>
45    /// <exception cref="InvalidOperationException">Thrown if the numbers in the permutation elements are not in the range [0;N) with N = length of the permutation.</exception>
46    /// <remarks>
47    /// First one segment is copied from the first parent to the offspring in the same position.
48    /// Then the tour is completed by adding the next number from the second parent if such an edge exists,
49    /// or from the first parent, or from the next number of the second parent.
50    /// The last case results in an unwanted mutation.
51    /// </remarks>
52    /// <param name="random">A random number generator.</param>
53    /// <param name="parent1">The first parent permutation to cross.</param>
54    /// <param name="parent2">The second parent permutation to cross.</param>
55    /// <returns>The new permutation resulting from the crossover.</returns>
56    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
57      if (parent1.Length != parent2.Length) throw new ArgumentException("MaximalPreservativeCrossover: The parent permutations are of unequal length.");
58      if (parent1.Length < 4) throw new ArgumentException("MaximalPreservativeCrossover: The parent permutation must be at least of size 4.");
59      int length = parent1.Length;
60      int[] result = new int[length];
61      bool[] numberCopied = new bool[length];
62      int breakPoint1, breakPoint2, subsegmentLength, index;
63
64      subsegmentLength = random.Next(3, Math.Max(length / 3, 4)); // as mentioned in Pohlheim, H. Evolutionäre Algorithmen: Verfahren, Operatoren und Hinweise für die Praxis, 1999, p.44, Springer.
65      breakPoint1 = random.Next(length);
66      breakPoint2 = breakPoint1 + subsegmentLength;
67      if (breakPoint2 >= length) breakPoint2 -= length;
68
69      // copy string between position [breakPoint1, breakPoint2) from parent1 to the offspring
70      index = breakPoint1;
71      do {
72        result[index] = parent1[index];
73        numberCopied[result[index]] = true;
74        index++;
75        if (index >= length) index -= length;
76      } while (index != breakPoint2);
77
78      // calculate inverse permutation (number -> index) to help finding the follower of a given number
79      int[] invParent1 = new int[length];
80      int[] invParent2 = new int[length];
81      try {
82        for (int i = 0; i < length; i++) {
83          invParent1[parent1[i]] = i;
84          invParent2[parent2[i]] = i;
85        }
86      } catch (IndexOutOfRangeException) {
87        throw new InvalidOperationException("MaximalPreservativeCrossover: The permutation must consist of numbers in the interval [0;N) with N = length of the permutation.");
88      }
89
90      int prevIndex = ((index > 0) ? (index - 1) : (length - 1));
91      do {
92        // look for the follower of the last number in parent2
93        int p2Follower = GetFollower(parent2, invParent2[result[prevIndex]]);
94        if (!numberCopied[p2Follower]) {
95          result[index] = p2Follower;
96        } else {
97          // if that follower has already been added, look for the follower of the last number in parent1
98          int p1Follower = GetFollower(parent1, invParent1[result[prevIndex]]);
99          if (!numberCopied[p1Follower]) {
100            result[index] = p1Follower;
101          } else {
102            // if that has also been added, look for the next not already added number in parent2
103            int tempIndex = index;
104            for (int i = 0; i < parent2.Length; i++) {
105              if (!numberCopied[parent2[tempIndex]]) {
106                result[index] = parent2[tempIndex];
107                break;
108              }
109              tempIndex++;
110              if (tempIndex >= parent2.Length) tempIndex = 0;
111            }
112          }
113        }
114        numberCopied[result[index]] = true;
115        prevIndex = index;
116        index++;
117        if (index >= length) index -= length;
118      } while (index != breakPoint1);
119
120      return new Permutation(result);
121    }
122
123    private static int GetFollower(Permutation parent, int index) {
124      if (index + 1 == parent.Length)
125        return parent[0];
126      return parent[index + 1];
127    }
128
129    /// <summary>
130    /// Checks number of parents and calls <see cref="Apply(IRandom, Permutation, Permutation)"/>.
131    /// </summary>
132    /// <exception cref="InvalidOperationException">Thrown if there are not exactly two permutations in <paramref name="parents"/>.</exception>
133    /// <param name="random">A random number generator.</param>
134    /// <param name="parents">An array containing the two permutations that should be crossed.</param>
135    /// <returns>The newly created permutation, resulting from the crossover operation.</returns>
136    protected override Permutation Cross(IRandom random, ItemArray<Permutation> parents) {
137      if (parents.Length != 2) throw new InvalidOperationException("MaximalPreservativeCrossover: Number of parents is not equal to 2.");
138      return Apply(random, parents[0], parents[1]);
139    }
140  }
141}
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