1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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26 |
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27 | namespace HeuristicLab.Encodings.RealVectorEncoding {
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28 | /// <summary>
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29 | /// The average crossover (intermediate recombination) calculates the average or centroid of a number of parent vectors.
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30 | /// </summary>
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31 | /// <remarks>
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32 | /// It is implemented as described by Beyer, H.-G. and Schwefel, H.-P. 2002. Evolution Strategies - A Comprehensive Introduction Natural Computing, 1, pp. 3-52.
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33 | /// </remarks>
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34 | [Item("AverageCrossover", "The average crossover (intermediate recombination) produces a new offspring by calculating in each position the average of a number of parents. It is implemented as described by Beyer, H.-G. and Schwefel, H.-P. 2002. Evolution Strategies - A Comprehensive Introduction Natural Computing, 1, pp. 3-52.")]
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35 | [StorableType("633EF75E-BD1A-4B89-86FA-EC785B4E2D28")]
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36 | public class AverageCrossover : RealVectorCrossover {
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37 | [StorableConstructor]
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38 | protected AverageCrossover(bool deserializing) : base(deserializing) { }
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39 | protected AverageCrossover(AverageCrossover original, Cloner cloner) : base(original, cloner) { }
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40 | public AverageCrossover() : base() { }
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41 |
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42 | public override IDeepCloneable Clone(Cloner cloner) {
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43 | return new AverageCrossover(this, cloner);
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44 | }
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45 |
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46 | /// <summary>
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47 | /// Performs the average crossover (intermediate recombination) on a list of parents.
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48 | /// </summary>
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49 | /// <exception cref="ArgumentException">Thrown when there is just one parent or when the parent vectors are of different length.</exception>
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50 | /// <remarks>
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51 | /// There can be more than two parents.
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52 | /// </remarks>
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53 | /// <param name="random">The random number generator.</param>
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54 | /// <param name="parents">The list of parents.</param>
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55 | /// <returns>The child vector (average) of the parents.</returns>
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56 | public static RealVector Apply(IRandom random, ItemArray<RealVector> parents) {
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57 | int length = parents[0].Length, parentsCount = parents.Length;
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58 | if (parents.Length < 2) throw new ArgumentException("AverageCrossover: The number of parents is less than 2.", "parents");
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59 | RealVector result = new RealVector(length);
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60 | try {
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61 | double avg;
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62 | for (int i = 0; i < length; i++) {
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63 | avg = 0;
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64 | for (int j = 0; j < parentsCount; j++)
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65 | avg += parents[j][i];
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66 | result[i] = avg / (double)parentsCount;
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67 | }
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68 | }
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69 | catch (IndexOutOfRangeException) {
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70 | throw new ArgumentException("AverageCrossover: The parents' vectors are of different length.", "parents");
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71 | }
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72 |
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73 | return result;
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74 | }
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75 |
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76 | /// <summary>
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77 | /// Forwards the call to <see cref="Apply(IRandom, ItemArray<RealVector>)"/>.
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78 | /// </summary>
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79 | /// <param name="random">The random number generator.</param>
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80 | /// <param name="parents">The list of parents.</param>
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81 | /// <returns>The child vector (average) of the parents.</returns>
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82 | protected override RealVector Cross(IRandom random, ItemArray<RealVector> parents) {
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83 | return Apply(random, parents);
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84 | }
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85 | }
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86 | }
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