1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 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.Linq;
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23 | using HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Operators;
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27 | using HeuristicLab.Optimization;
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28 | using HeuristicLab.Parameters;
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29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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30 |
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31 | namespace HeuristicLab.Algorithms.RAPGA {
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32 | /// <summary>
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33 | /// An operator that progressively selects offspring by adding it to a scope list.
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34 | /// </summary>
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35 | /// <remarks>
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36 | /// The operator also performs duplication control.
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37 | /// </remarks>
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38 | [Item("ProgressiveOffspringPreserver", "An operator that progressively selects offspring by adding it to a scope list. The operator also performs duplication control.")]
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39 | [StorableClass]
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40 | public sealed class ProgressiveOffspringPreserver : SingleSuccessorOperator, ISimilarityBasedOperator {
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41 | #region ISimilarityBasedOperator Members
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42 | [Storable]
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43 | public ISolutionSimilarityCalculator SimilarityCalculator { get; set; }
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44 | #endregion
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45 |
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46 | #region Parameter Properties
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47 | public ScopeParameter CurrentScopeParameter {
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48 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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49 | }
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50 | public ILookupParameter<ScopeList> OffspringListParameter {
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51 | get { return (ILookupParameter<ScopeList>)Parameters["OffspringList"]; }
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52 | }
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53 | public ILookupParameter<IntValue> ElitesParameter {
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54 | get { return (ILookupParameter<IntValue>)Parameters["Elites"]; }
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55 | }
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56 | public ILookupParameter<IntValue> MaximumPopulationSizeParameter {
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57 | get { return (ILookupParameter<IntValue>)Parameters["MaximumPopulationSize"]; }
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58 | }
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59 | #endregion
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60 |
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61 | #region Properties
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62 | private IScope CurrentScope {
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63 | get { return CurrentScopeParameter.ActualValue; }
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64 | }
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65 | private ScopeList OffspringList {
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66 | get { return OffspringListParameter.ActualValue; }
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67 | }
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68 | private IntValue Elites {
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69 | get { return ElitesParameter.ActualValue; }
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70 | }
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71 | private IntValue MaximumPopulationSize {
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72 | get { return MaximumPopulationSizeParameter.ActualValue; }
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73 | }
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74 | #endregion
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75 |
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76 | [StorableConstructor]
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77 | private ProgressiveOffspringPreserver(bool deserializing) : base(deserializing) { }
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78 | private ProgressiveOffspringPreserver(ProgressiveOffspringPreserver original, Cloner cloner)
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79 | : base(original, cloner) {
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80 | this.SimilarityCalculator = cloner.Clone(original.SimilarityCalculator);
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81 | }
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82 | public ProgressiveOffspringPreserver()
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83 | : base() {
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84 | Parameters.Add(new ScopeParameter("CurrentScope", "The current scope that contains the offspring."));
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85 | Parameters.Add(new LookupParameter<ScopeList>("OffspringList", "The list that contains the offspring."));
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86 | Parameters.Add(new LookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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87 | Parameters.Add(new LookupParameter<IntValue>("MaximumPopulationSize", "The maximum size of the population of solutions."));
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88 | }
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89 |
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90 | public override IDeepCloneable Clone(Cloner cloner) {
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91 | return new ProgressiveOffspringPreserver(this, cloner);
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92 | }
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93 |
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94 | public override IOperation Apply() {
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95 | if (CurrentScope.SubScopes.Any()) { // offspring created
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96 | if (!OffspringList.Any()) OffspringList.AddRange(CurrentScope.SubScopes);
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97 | else { // stored offspring exists
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98 | var storedOffspringScope = new Scope();
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99 | storedOffspringScope.SubScopes.AddRange(OffspringList);
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100 | var similarityMatrix = SimilarityCalculator.CalculateSolutionCrowdSimilarity(CurrentScope, storedOffspringScope);
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101 |
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102 | var createdOffspring = CurrentScope.SubScopes.ToArray();
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103 |
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104 | int i = 0;
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105 | // as long as offspring is available and not enough offspring has been preserved
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106 | while (i < createdOffspring.Length && OffspringList.Count < MaximumPopulationSize.Value - Elites.Value) {
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107 | if (similarityMatrix[i].Any(x => x.IsAlmost(1.0))) createdOffspring[i] = null; // discard duplicates
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108 | else OffspringList.Add(createdOffspring[i]);
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109 | i++;
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110 | }
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111 |
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112 | // discard remaining offspring
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113 | while (i < createdOffspring.Length) createdOffspring[i++] = null;
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114 |
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115 | // clean current scope
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116 | CurrentScope.SubScopes.Replace(createdOffspring.Where(x => x != null));
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117 | }
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118 | }
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119 | return base.Apply();
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120 | }
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121 | }
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122 | } |
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