1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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 HEAL.Attic;
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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.Operators;
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28 | using HeuristicLab.Parameters;
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29 | using HeuristicLab.Selection;
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30 |
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31 | namespace HeuristicLab.Algorithms.ALPS {
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32 | /// <summary>
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33 | /// An operator which represents the main loop of an offspring selection genetic algorithm.
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34 | /// </summary>
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35 | [Item("AlpsOffspringSelectionGeneticAlgorithmMainOperator", "An operator that represents the core of an alps offspring selection genetic algorithm.")]
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36 | [StorableType("4DBAA32D-84EB-40C0-838D-ACCF9A9C41FA")]
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37 | public sealed class AlpsOffspringSelectionGeneticAlgorithmMainOperator : AlgorithmOperator {
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38 | #region Parameter properties
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39 | public IValueLookupParameter<IRandom> RandomParameter {
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40 | get { return (IValueLookupParameter<IRandom>)Parameters["Random"]; }
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41 | }
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42 | public IValueLookupParameter<IOperator> EvaluatorParameter {
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43 | get { return (IValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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44 | }
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45 | public ILookupParameter<IntValue> EvaluatedSolutionsParameter {
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46 | get { return (ILookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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47 | }
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48 | public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
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49 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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50 | }
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51 | public IValueLookupParameter<BoolValue> MaximizationParameter {
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52 | get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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53 | }
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54 |
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55 | public ILookupParameter<IntValue> PopulationSizeParameter {
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56 | get { return (ILookupParameter<IntValue>)Parameters["PopulationSize"]; }
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57 | }
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58 |
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59 | public IValueLookupParameter<IOperator> SelectorParameter {
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60 | get { return (IValueLookupParameter<IOperator>)Parameters["Selector"]; }
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61 | }
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62 | public IValueLookupParameter<IOperator> CrossoverParameter {
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63 | get { return (IValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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64 | }
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65 | public IValueLookupParameter<IOperator> MutatorParameter {
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66 | get { return (IValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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67 | }
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68 | public IValueLookupParameter<PercentValue> MutationProbabilityParameter {
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69 | get { return (IValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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70 | }
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71 | public IValueLookupParameter<IntValue> ElitesParameter {
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72 | get { return (IValueLookupParameter<IntValue>)Parameters["Elites"]; }
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73 | }
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74 | public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
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75 | get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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76 | }
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77 |
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78 | public ILookupParameter<DoubleValue> ComparisonFactorParameter {
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79 | get { return (ILookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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80 | }
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81 | public ILookupParameter<DoubleValue> CurrentSuccessRatioParameter {
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82 | get { return (ILookupParameter<DoubleValue>)Parameters["CurrentSuccessRatio"]; }
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83 | }
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84 | public IValueLookupParameter<DoubleValue> SuccessRatioParameter {
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85 | get { return (IValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
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86 | }
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87 | public ILookupParameter<DoubleValue> SelectionPressureParameter {
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88 | get { return (ILookupParameter<DoubleValue>)Parameters["SelectionPressure"]; }
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89 | }
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90 | public IValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
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91 | get { return (IValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
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92 | }
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93 | public IValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
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94 | get { return (IValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
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95 | }
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96 | public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
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97 | get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
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98 | }
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99 |
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100 | public IScopeTreeLookupParameter<DoubleValue> AgeParameter {
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101 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Age"]; }
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102 | }
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103 | public IValueLookupParameter<DoubleValue> AgeInheritanceParameter {
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104 | get { return (IValueLookupParameter<DoubleValue>)Parameters["AgeInheritance"]; }
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105 | }
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106 | public IValueLookupParameter<DoubleValue> AgeIncrementParameter {
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107 | get { return (IValueLookupParameter<DoubleValue>)Parameters["AgeIncrement"]; }
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108 | }
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109 | #endregion
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110 |
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111 | [StorableConstructor]
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112 | private AlpsOffspringSelectionGeneticAlgorithmMainOperator(StorableConstructorFlag _) : base(_) { }
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113 | private AlpsOffspringSelectionGeneticAlgorithmMainOperator(AlpsOffspringSelectionGeneticAlgorithmMainOperator original, Cloner cloner)
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114 | : base(original, cloner) {
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115 | }
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116 | public override IDeepCloneable Clone(Cloner cloner) {
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117 | return new AlpsOffspringSelectionGeneticAlgorithmMainOperator(this, cloner);
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118 | }
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119 | public AlpsOffspringSelectionGeneticAlgorithmMainOperator()
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120 | : base() {
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121 | Initialize();
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122 | }
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123 |
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124 | private void Initialize() {
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125 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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126 |
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127 | Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
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128 | Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
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129 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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130 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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131 |
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132 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population of solutions in each layer."));
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133 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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134 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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135 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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136 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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137 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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138 | Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
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139 |
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140 | Parameters.Add(new LookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1]."));
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141 | Parameters.Add(new LookupParameter<DoubleValue>("CurrentSuccessRatio", "The current success ratio."));
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142 | Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
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143 | Parameters.Add(new LookupParameter<DoubleValue>("SelectionPressure", "The actual selection pressure."));
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144 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
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145 | Parameters.Add(new ValueLookupParameter<BoolValue>("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation."));
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146 | Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
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147 |
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148 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Age", "The age of individuals."));
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149 | Parameters.Add(new ValueLookupParameter<DoubleValue>("AgeInheritance", "A weight that determines the age of a child after crossover based on the older (1.0) and younger (0.0) parent."));
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150 | Parameters.Add(new ValueLookupParameter<DoubleValue>("AgeIncrement", "The value the age the individuals is incremented if they survives a generation."));
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151 |
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152 |
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153 | var selector = new Placeholder();
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154 | var subScopesProcessor1 = new SubScopesProcessor();
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155 | var childrenCreator = new ChildrenCreator();
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156 | var osBeforeMutationBranch = new ConditionalBranch();
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157 | var uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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158 | var crossover1 = new Placeholder();
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159 | var uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
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160 | var evaluator1 = new Placeholder();
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161 | var subScopesCounter1 = new SubScopesCounter();
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162 | var qualityComparer1 = new WeightedParentsQualityComparator();
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163 | var ageCalculator1 = new WeightingReducer() { Name = "Calculate Age" };
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164 | var subScopesRemover1 = new SubScopesRemover();
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165 | var uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
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166 | var mutationBranch1 = new StochasticBranch();
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167 | var mutator1 = new Placeholder();
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168 | var variableCreator1 = new VariableCreator();
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169 | var variableCreator2 = new VariableCreator();
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170 | var conditionalSelector = new ConditionalSelector();
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171 | var subScopesProcessor2 = new SubScopesProcessor();
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172 | var uniformSubScopesProcessor4 = new UniformSubScopesProcessor();
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173 | var evaluator2 = new Placeholder();
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174 | var subScopesCounter2 = new SubScopesCounter();
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175 | var mergingReducer1 = new MergingReducer();
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176 | var uniformSubScopesProcessor5 = new UniformSubScopesProcessor();
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177 | var crossover2 = new Placeholder();
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178 | var mutationBranch2 = new StochasticBranch();
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179 | var mutator2 = new Placeholder();
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180 | var uniformSubScopesProcessor6 = new UniformSubScopesProcessor();
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181 | var evaluator3 = new Placeholder();
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182 | var subScopesCounter3 = new SubScopesCounter();
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183 | var qualityComparer2 = new WeightedParentsQualityComparator();
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184 | var ageCalculator2 = new WeightingReducer() { Name = "Calculate Age" };
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185 | var subScopesRemover2 = new SubScopesRemover();
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186 | var offspringSelector = new AlpsOffspringSelector();
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187 | var subScopesProcessor3 = new SubScopesProcessor();
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188 | var bestSelector = new BestSelector();
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189 | var worstSelector = new WorstSelector();
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190 | var rightReducer = new RightReducer();
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191 | var leftReducer = new LeftReducer();
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192 | var mergingReducer2 = new MergingReducer();
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193 | var reevaluateElitesBranch = new ConditionalBranch();
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194 | var uniformSubScopesProcessor7 = new UniformSubScopesProcessor();
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195 | var evaluator4 = new Placeholder();
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196 | var subScopesCounter4 = new SubScopesCounter();
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197 | var incrementAgeProcessor = new UniformSubScopesProcessor();
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198 | var ageIncrementor = new DoubleCounter() { Name = "Increment Age" };
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199 |
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200 |
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201 | OperatorGraph.InitialOperator = selector;
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202 |
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203 | selector.Name = "Selector (placeholder)";
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204 | selector.OperatorParameter.ActualName = SelectorParameter.Name;
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205 | selector.Successor = subScopesProcessor1;
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206 |
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207 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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208 | subScopesProcessor1.Operators.Add(childrenCreator);
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209 | subScopesProcessor1.Successor = offspringSelector;
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210 |
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211 | childrenCreator.ParentsPerChild = new IntValue(2);
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212 | childrenCreator.Successor = osBeforeMutationBranch;
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213 |
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214 | osBeforeMutationBranch.Name = "Apply OS before mutation?";
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215 | osBeforeMutationBranch.ConditionParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
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216 | osBeforeMutationBranch.TrueBranch = uniformSubScopesProcessor1;
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217 | osBeforeMutationBranch.FalseBranch = uniformSubScopesProcessor5;
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218 | osBeforeMutationBranch.Successor = null;
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219 |
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220 | uniformSubScopesProcessor1.Operator = crossover1;
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221 | uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
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222 |
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223 | crossover1.Name = "Crossover (placeholder)";
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224 | crossover1.OperatorParameter.ActualName = CrossoverParameter.Name;
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225 | crossover1.Successor = null;
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226 |
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227 | uniformSubScopesProcessor2.Parallel.Value = true;
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228 | uniformSubScopesProcessor2.Operator = evaluator1;
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229 | uniformSubScopesProcessor2.Successor = subScopesCounter1;
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230 |
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231 | evaluator1.Name = "Evaluator (placeholder)";
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232 | evaluator1.OperatorParameter.ActualName = EvaluatorParameter.Name;
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233 | evaluator1.Successor = qualityComparer1;
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234 |
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235 | subScopesCounter1.Name = "Increment EvaluatedSolutions";
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236 | subScopesCounter1.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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237 | subScopesCounter1.Successor = uniformSubScopesProcessor3;
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238 |
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239 | uniformSubScopesProcessor3.Operator = mutationBranch1;
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240 | uniformSubScopesProcessor3.Successor = conditionalSelector;
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241 |
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242 | qualityComparer1.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
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243 | qualityComparer1.LeftSideParameter.ActualName = QualityParameter.Name;
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244 | qualityComparer1.MaximizationParameter.ActualName = MaximizationParameter.Name;
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245 | qualityComparer1.RightSideParameter.ActualName = QualityParameter.Name;
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246 | qualityComparer1.ResultParameter.ActualName = "SuccessfulOffspring";
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247 | qualityComparer1.Successor = ageCalculator1;
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248 |
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249 | ageCalculator1.ParameterToReduce.ActualName = AgeParameter.Name;
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250 | ageCalculator1.TargetParameter.ActualName = AgeParameter.Name;
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251 | ageCalculator1.WeightParameter.ActualName = AgeInheritanceParameter.Name;
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252 | ageCalculator1.Successor = subScopesRemover1;
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253 |
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254 | subScopesRemover1.RemoveAllSubScopes = true;
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255 | subScopesRemover1.Successor = null;
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256 |
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257 | mutationBranch1.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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258 | mutationBranch1.RandomParameter.ActualName = RandomParameter.Name;
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259 | mutationBranch1.FirstBranch = mutator1;
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260 | mutationBranch1.SecondBranch = variableCreator2;
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261 | mutationBranch1.Successor = null;
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262 |
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263 | mutator1.Name = "Mutator (placeholder)";
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264 | mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
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265 | mutator1.Successor = variableCreator1;
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266 |
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267 | variableCreator1.Name = "MutatedOffspring = true";
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268 | variableCreator1.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(true)) { GetsCollected = false });
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269 | variableCreator1.Successor = null;
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270 |
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271 | variableCreator2.Name = "MutatedOffspring = false";
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272 | variableCreator2.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(false)) { GetsCollected = false });
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273 | variableCreator2.Successor = null;
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274 |
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275 | conditionalSelector.ConditionParameter.ActualName = "MutatedOffspring";
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276 | conditionalSelector.ConditionParameter.Depth = 1;
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277 | conditionalSelector.CopySelected.Value = false;
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278 | conditionalSelector.Successor = subScopesProcessor2;
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279 |
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280 | subScopesProcessor2.Operators.Add(new EmptyOperator());
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281 | subScopesProcessor2.Operators.Add(uniformSubScopesProcessor4);
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282 | subScopesProcessor2.Successor = mergingReducer1;
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283 |
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284 | mergingReducer1.Successor = null;
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285 |
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286 | uniformSubScopesProcessor4.Parallel.Value = true;
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287 | uniformSubScopesProcessor4.Operator = evaluator2;
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288 | uniformSubScopesProcessor4.Successor = subScopesCounter2;
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289 |
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290 | evaluator2.Name = "Evaluator (placeholder)";
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291 | evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
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292 | evaluator2.Successor = null;
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293 |
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294 | subScopesCounter2.Name = "Increment EvaluatedSolutions";
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295 | subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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296 | subScopesCounter2.Successor = null;
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297 |
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298 | uniformSubScopesProcessor5.Operator = crossover2;
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299 | uniformSubScopesProcessor5.Successor = uniformSubScopesProcessor6;
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300 |
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301 | crossover2.Name = "Crossover (placeholder)";
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302 | crossover2.OperatorParameter.ActualName = CrossoverParameter.Name;
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303 | crossover2.Successor = mutationBranch2;
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304 |
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305 | mutationBranch2.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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306 | mutationBranch2.RandomParameter.ActualName = RandomParameter.Name;
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307 | mutationBranch2.FirstBranch = mutator2;
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308 | mutationBranch2.SecondBranch = null;
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309 | mutationBranch2.Successor = null;
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310 |
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311 | mutator2.Name = "Mutator (placeholder)";
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312 | mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
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313 | mutator2.Successor = null;
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314 |
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315 | uniformSubScopesProcessor6.Parallel.Value = true;
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316 | uniformSubScopesProcessor6.Operator = evaluator3;
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317 | uniformSubScopesProcessor6.Successor = subScopesCounter3;
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318 |
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319 | evaluator3.Name = "Evaluator (placeholder)";
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320 | evaluator3.OperatorParameter.ActualName = EvaluatorParameter.Name;
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321 | evaluator3.Successor = qualityComparer2;
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322 |
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323 | subScopesCounter3.Name = "Increment EvaluatedSolutions";
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324 | subScopesCounter3.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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325 |
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326 | qualityComparer2.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
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327 | qualityComparer2.LeftSideParameter.ActualName = QualityParameter.Name;
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328 | qualityComparer2.MaximizationParameter.ActualName = MaximizationParameter.Name;
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329 | qualityComparer2.RightSideParameter.ActualName = QualityParameter.Name;
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330 | qualityComparer2.ResultParameter.ActualName = "SuccessfulOffspring";
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331 | qualityComparer2.Successor = ageCalculator2;
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332 |
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333 | ageCalculator2.ParameterToReduce.ActualName = AgeParameter.Name;
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334 | ageCalculator2.TargetParameter.ActualName = AgeParameter.Name;
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335 | ageCalculator2.WeightParameter.ActualName = AgeInheritanceParameter.Name;
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336 | ageCalculator2.Successor = subScopesRemover2;
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337 |
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338 | subScopesRemover2.RemoveAllSubScopes = true;
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339 | subScopesRemover2.Successor = null;
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340 |
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341 | subScopesCounter3.Successor = null;
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342 |
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343 | offspringSelector.CurrentSuccessRatioParameter.ActualName = CurrentSuccessRatioParameter.Name;
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344 | offspringSelector.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
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345 | offspringSelector.SelectionPressureParameter.ActualName = SelectionPressureParameter.Name;
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346 | offspringSelector.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
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347 | offspringSelector.OffspringPopulationParameter.ActualName = "OffspringPopulation";
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348 | offspringSelector.OffspringPopulationWinnersParameter.ActualName = "OffspringPopulationWinners";
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349 | offspringSelector.SuccessfulOffspringParameter.ActualName = "SuccessfulOffspring";
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350 | offspringSelector.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
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351 | offspringSelector.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
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352 | offspringSelector.OffspringCreator = selector;
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353 | offspringSelector.Successor = subScopesProcessor3;
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354 |
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355 | subScopesProcessor3.Operators.Add(bestSelector);
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356 | subScopesProcessor3.Operators.Add(worstSelector);
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357 | subScopesProcessor3.Successor = mergingReducer2;
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358 |
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359 | bestSelector.CopySelected = new BoolValue(false);
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360 | bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
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361 | bestSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
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362 | bestSelector.QualityParameter.ActualName = QualityParameter.Name;
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363 | bestSelector.Successor = rightReducer;
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364 |
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365 | rightReducer.Successor = reevaluateElitesBranch;
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366 |
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367 | reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
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368 | reevaluateElitesBranch.Name = "Reevaluate elites ?";
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369 | reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor7;
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370 | reevaluateElitesBranch.FalseBranch = null;
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371 | reevaluateElitesBranch.Successor = null;
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372 |
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373 | uniformSubScopesProcessor7.Parallel.Value = true;
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374 | uniformSubScopesProcessor7.Operator = evaluator4;
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375 | uniformSubScopesProcessor7.Successor = subScopesCounter4;
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376 |
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377 | evaluator4.Name = "Evaluator (placeholder)";
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378 | evaluator4.OperatorParameter.ActualName = EvaluatorParameter.Name;
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379 |
|
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380 | subScopesCounter4.Name = "Increment EvaluatedSolutions";
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381 | subScopesCounter4.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
|
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382 | subScopesCounter4.Successor = null;
|
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383 |
|
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384 | worstSelector.CopySelected = new BoolValue(false);
|
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385 | worstSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
|
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386 | worstSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
|
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387 | worstSelector.QualityParameter.ActualName = QualityParameter.Name;
|
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388 | worstSelector.Successor = leftReducer;
|
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389 |
|
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390 | leftReducer.Successor = null;
|
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391 |
|
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392 | mergingReducer2.Successor = incrementAgeProcessor;
|
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393 |
|
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394 | incrementAgeProcessor.Operator = ageIncrementor;
|
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395 | incrementAgeProcessor.Successor = null;
|
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396 |
|
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397 | ageIncrementor.ValueParameter.ActualName = AgeParameter.Name;
|
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398 | ageIncrementor.IncrementParameter.Value = null;
|
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399 | ageIncrementor.IncrementParameter.ActualName = AgeIncrementParameter.Name;
|
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400 | ageIncrementor.Successor = null;
|
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401 | }
|
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402 |
|
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403 | public override IOperation Apply() {
|
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404 | if (CrossoverParameter.ActualValue == null)
|
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405 | return null;
|
---|
406 | return base.Apply();
|
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407 | }
|
---|
408 | }
|
---|
409 | }
|
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