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 |
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Encodings.PermutationEncoding;
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29 | using HeuristicLab.Operators;
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30 | using HeuristicLab.Optimization;
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31 | using HeuristicLab.Optimization.Operators;
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32 | using HeuristicLab.Parameters;
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33 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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34 | using HeuristicLab.Problems.TravelingSalesman;
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35 |
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36 | namespace HeuristicLab.Analysis.AlgorithmBehavior.Analyzers {
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37 | [Item("CrossoverPerformanceAnalyzer", "An operator that analyzes the performance of crossovers.")]
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38 | [StorableClass]
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39 | public class CrossoverPerformanceAnalyzer : SingleSuccessorOperator, IAnalyzer {
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40 | private const string ResultsParameterName = "Results";
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41 | private const string GenerationsParameterName = "Generations";
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42 |
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43 | #region IAnalyzer Members
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44 | public bool EnabledByDefault {
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45 | get { return true; }
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46 | }
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47 | #endregion
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48 |
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49 | #region Parameter properties
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50 | public ILookupParameter<ResultCollection> ResultsParameter {
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51 | get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
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52 | }
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53 | public ILookupParameter<IntValue> GenerationsParameter {
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54 | get { return (ILookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
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55 | }
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56 | public ILookupParameter<ItemArray<Permutation>> ParentsParameter {
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57 | get { return (ScopeTreeLookupParameter<Permutation>)Parameters["Parents"]; }
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58 | }
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59 | public ILookupParameter<ItemArray<DoubleValue>> ParentsQualityParameter {
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60 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["ParentsQuality"]; }
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61 | }
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62 | public ILookupParameter<Permutation> ChildParameter {
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63 | get { return ((LookupParameter<Permutation>)Parameters["Child"]); }
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64 | }
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65 | public ILookupParameter<DoubleValue> QualityParameter {
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66 | get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
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67 | }
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68 | public IValueParameter<SingleObjectiveSolutionSimilarityCalculator> SimilarityCalculatorParameter {
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69 | get { return (IValueParameter<SingleObjectiveSolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
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70 | }
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71 | #endregion
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72 |
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73 | #region Properties
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74 | public ResultCollection Results {
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75 | get { return ResultsParameter.ActualValue; }
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76 | }
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77 | #endregion
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78 |
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79 | [Storable]
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80 | private ScatterPlotHelper plotHelper, childDiversityHelper, parentDiversityHelper;
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81 | [Storable]
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82 | private DataTableHelper performanceHelper, successHelper, equalParentsHelper;
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83 | [Storable]
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84 | private int cnt = 0;
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85 | [Storable]
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86 | private int success = 0;
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87 | [Storable]
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88 | private int lastGeneration = 0;
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89 | [Storable]
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90 | private int equalParents = 0;
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91 | [Storable]
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92 | private List<double> qualityPoints = new List<double>();
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93 |
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94 | [StorableConstructor]
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95 | private CrossoverPerformanceAnalyzer(bool deserializing) : base(deserializing) { }
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96 | private CrossoverPerformanceAnalyzer(CrossoverPerformanceAnalyzer original, Cloner cloner)
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97 | : base(original, cloner) {
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98 | cnt = original.cnt;
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99 | success = original.success;
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100 | lastGeneration = original.lastGeneration;
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101 | equalParents = original.equalParents;
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102 | qualityPoints = new List<double>(original.qualityPoints);
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103 | plotHelper = (ScatterPlotHelper)original.plotHelper.Clone(cloner);
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104 | childDiversityHelper = (ScatterPlotHelper)original.childDiversityHelper.Clone(cloner);
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105 | parentDiversityHelper = (ScatterPlotHelper)original.parentDiversityHelper.Clone(cloner);
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106 | performanceHelper = (DataTableHelper)original.performanceHelper.Clone(cloner);
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107 | successHelper = (DataTableHelper)original.successHelper.Clone(cloner);
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108 | equalParentsHelper = (DataTableHelper)original.equalParentsHelper.Clone(cloner);
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109 | }
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110 |
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111 | public CrossoverPerformanceAnalyzer()
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112 | : base() {
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113 | Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The results collection where the analysis values should be stored."));
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114 | Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "Nr of generations."));
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115 |
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116 | Parameters.Add(new ScopeTreeLookupParameter<Permutation>("Parents", "The parent permutations which have been crossed."));
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117 | ParentsParameter.ActualName = "TSPTour";
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118 |
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119 | Parameters.Add(new LookupParameter<Permutation>("Child", "The child permutation resulting from the crossover."));
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120 | ChildParameter.ActualName = "TSPTour";
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121 |
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122 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("ParentsQuality", "The quality of the parent solutions."));
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123 | ParentsQualityParameter.ActualName = "TSPTourLength";
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124 |
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125 | Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The evaluated quality of the child solution."));
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126 | QualityParameter.ActualName = "TSPTourLength";
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127 |
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128 | Parameters.Add(new ValueParameter<SingleObjectiveSolutionSimilarityCalculator>("SimilarityCalculator"));
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129 |
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130 | plotHelper = new ScatterPlotHelper(false, true);
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131 | childDiversityHelper = new ScatterPlotHelper(false, true);
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132 | parentDiversityHelper = new ScatterPlotHelper(false, true);
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133 | performanceHelper = new DataTableHelper();
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134 | successHelper = new DataTableHelper();
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135 | equalParentsHelper = new DataTableHelper();
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136 | }
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137 |
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138 | public override IDeepCloneable Clone(Cloner cloner) {
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139 | return new CrossoverPerformanceAnalyzer(this, cloner);
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140 | }
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141 |
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142 | public override IOperation Apply() {
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143 | SimilarityCalculatorParameter.Value.QualityVariableName = "TSPTourLength";
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144 | SimilarityCalculatorParameter.Value.SolutionVariableName = "TSPTour";
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145 |
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146 | plotHelper.InitializePlot(Results, "Crossover Performance", "Solution Index", "Absolut Quality Difference");
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147 | childDiversityHelper.InitializePlot(Results, "Child Diversity", "Solution Index", "Diversity");
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148 | parentDiversityHelper.InitializePlot(Results, "Parent Diversity", "Solution Index", "Diversity");
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149 |
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150 | performanceHelper.InitializeChart(Results, "Average Crossover Performance", "Average Crossover Performance per Generation");
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151 | successHelper.InitializeChart(Results, "Successfull Crossovers", "Successfull Crossovers per Generation");
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152 | equalParentsHelper.InitializeChart(Results, "Number of equal parents", "Absolut number of equal parents");
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153 |
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154 | Point2D<double> qualityPoint, diversityPointChild, diversityPointParent;
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155 | var qualityParent1 = ParentsQualityParameter.ActualValue.First().Value;
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156 | var qualityParent2 = ParentsQualityParameter.ActualValue.Last().Value;
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157 | var child = ChildParameter.ActualValue;
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158 | var parent1 = ParentsParameter.ActualValue.First();
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159 | var parent2 = ParentsParameter.ActualValue.Last();
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160 | var parentDiversity = SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope.SubScopes.First(), ExecutionContext.Scope.SubScopes.Last());
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161 | string curGenStr = GenerationsParameter.ActualValue.Value.ToString();
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162 |
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163 |
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164 | diversityPointParent = new Point2D<double>(cnt, parentDiversity);
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165 | double worseQuality = qualityParent1 > qualityParent2 ? qualityParent1 : qualityParent2;
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166 | if (qualityParent1 > qualityParent2) {
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167 | diversityPointChild = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.First()));
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168 | } else {
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169 | diversityPointChild = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.Last()));
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170 | }
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171 |
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172 | qualityPoint = new Point2D<double>(cnt++, worseQuality - QualityParameter.ActualValue.Value);
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173 | if ((worseQuality - QualityParameter.ActualValue.Value) > 0) {
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174 | success++;
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175 | }
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176 | qualityPoints.Add(qualityPoint.Y);
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177 |
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178 | if (TSPSimilarityCalculator.CalculateSimilarity(parent1, parent2) == 1.0) {
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179 | equalParents++;
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180 | }
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181 |
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182 | if (GenerationsParameter.ActualValue.Value != 0) {
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183 | if (GenerationsParameter.ActualValue.Value > lastGeneration) {
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184 | double avg = qualityPoints.Average();
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185 |
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186 | performanceHelper.AddPoint(avg);
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187 | successHelper.AddPoint(success);
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188 | equalParentsHelper.AddPoint(equalParents);
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189 |
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190 | Reset();
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191 | }
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192 |
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193 | plotHelper.AddPoint(curGenStr, qualityPoint);
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194 | childDiversityHelper.AddPoint(curGenStr, diversityPointChild);
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195 | parentDiversityHelper.AddPoint(curGenStr, diversityPointParent);
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196 | } else {
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197 | Reset();
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198 | }
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199 |
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200 | return base.Apply();
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201 | }
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202 |
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203 | private void Reset() {
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204 | cnt = 0;
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205 | success = 0;
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206 | lastGeneration = GenerationsParameter.ActualValue.Value;
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207 | qualityPoints.Clear();
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208 | equalParents = 0;
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209 | }
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210 | }
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211 | }
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