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source: trunk/sources/HeuristicLab.Encodings.PermutationEncoding/3.3/Crossovers/MaximalPreservativeCrossover.cs @ 4068

Last change on this file since 4068 was 4068, checked in by swagner, 14 years ago

Sorted usings and removed unused usings in entire solution (#1094)

File size: 7.7 KB
Line 
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  public class MaximalPreservativeCrossover : PermutationCrossover {
39    /// <summary>
40    /// Performs the maximal preservative crossover on <paramref name="parent1"/> and <paramref name="parent2"/>
41    /// by preserving a large number of edges in both parents.
42    /// </summary>
43    /// <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>
44    /// <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>
45    /// <remarks>
46    /// First one segment is copied from the first parent to the offspring in the same position.
47    /// Then the tour is completed by adding the next number from the second parent if such an edge exists,
48    /// or from the first parent, or from the next number of the second parent.
49    /// The last case results in an unwanted mutation.
50    /// </remarks>
51    /// <param name="random">A random number generator.</param>
52    /// <param name="parent1">The first parent permutation to cross.</param>
53    /// <param name="parent2">The second parent permutation to cross.</param>
54    /// <returns>The new permutation resulting from the crossover.</returns>
55    public static Permutation Apply(IRandom random, Permutation parent1, Permutation parent2) {
56      if (parent1.Length != parent2.Length) throw new ArgumentException("MaximalPreservativeCrossover: The parent permutations are of unequal length.");
57      if (parent1.Length < 4) throw new ArgumentException("MaximalPreservativeCrossover: The parent permutation must be at least of size 4.");
58      int length = parent1.Length;
59      int[] result = new int[length];
60      bool[] numberCopied = new bool[length];
61      int breakPoint1, breakPoint2, subsegmentLength, index;
62
63      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.
64      breakPoint1 = random.Next(length);
65      breakPoint2 = breakPoint1 + subsegmentLength;
66      if (breakPoint2 >= length) breakPoint2 -= length;
67
68      // copy string between position [breakPoint1, breakPoint2) from parent1 to the offspring
69      index = breakPoint1;
70      do {
71        result[index] = parent1[index];
72        numberCopied[result[index]] = true;
73        index++;
74        if (index >= length) index -= length;
75      } while (index != breakPoint2);
76
77      // calculate inverse permutation (number -> index) to help finding the follower of a given number
78      int[] invParent1 = new int[length];
79      int[] invParent2 = new int[length];
80      try {
81        for (int i = 0; i < length; i++) {
82          invParent1[parent1[i]] = i;
83          invParent2[parent2[i]] = i;
84        }
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(parent1.PermutationType, 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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