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