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 | using System;
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22 | using HEAL.Attic;
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23 | using HeuristicLab.Analysis;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.Encodings.RealVectorEncoding;
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28 | using HeuristicLab.Optimization;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Problems.Instances;
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31 |
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32 | namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
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33 | [StorableType("AB0C6A73-C432-46FD-AE3B-9841EAB2478C")]
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34 | [Creatable(CreatableAttribute.Categories.Problems, Priority = 95)]
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35 | [Item("Test Function (multi-objective)", "Test functions with real valued inputs and multiple objectives.")]
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36 | public class MultiObjectiveTestFunctionProblem : RealVectorMultiObjectiveProblem, IProblemInstanceConsumer<MOTFData>, IMultiObjectiveProblemDefinition<RealVectorEncoding, RealVector> {
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37 | #region Parameter Properties
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38 | public IFixedValueParameter<IntValue> ProblemSizeParameter {
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39 | get { return (IFixedValueParameter<IntValue>)Parameters["ProblemSize"]; }
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40 | }
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41 | public IFixedValueParameter<IntValue> ObjectivesParameter {
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42 | get { return (IFixedValueParameter<IntValue>)Parameters["Objectives"]; }
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43 | }
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44 | public IValueParameter<DoubleMatrix> BoundsParameter {
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45 | get { return (IValueParameter<DoubleMatrix>)Parameters["Bounds"]; }
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46 | }
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47 | public IValueParameter<IMultiObjectiveTestFunction> TestFunctionParameter {
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48 | get { return (IValueParameter<IMultiObjectiveTestFunction>)Parameters["TestFunction"]; }
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49 | }
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50 | #endregion
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51 |
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52 | #region Properties
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53 | public int ProblemSize {
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54 | get { return ProblemSizeParameter.Value.Value; }
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55 | set { ProblemSizeParameter.Value.Value = value; }
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56 | }
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57 | public new int Objectives {
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58 | get { return ObjectivesParameter.Value.Value; }
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59 | set { ObjectivesParameter.Value.Value = value; }
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60 | }
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61 | public DoubleMatrix Bounds {
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62 | get { return BoundsParameter.Value; }
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63 | set { BoundsParameter.Value = value; }
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64 | }
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65 | public IMultiObjectiveTestFunction TestFunction {
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66 | get { return TestFunctionParameter.Value; }
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67 | set { TestFunctionParameter.Value = value; }
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68 | }
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69 | #endregion
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70 |
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71 | [StorableConstructor]
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72 | protected MultiObjectiveTestFunctionProblem(StorableConstructorFlag _) : base(_) { }
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73 | [StorableHook(HookType.AfterDeserialization)]
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74 | private void AfterDeserialization() {
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75 | RegisterEventHandlers();
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76 | }
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77 |
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78 | protected MultiObjectiveTestFunctionProblem(MultiObjectiveTestFunctionProblem original, Cloner cloner) : base(original, cloner) {
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79 | RegisterEventHandlers();
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80 | }
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81 | public override IDeepCloneable Clone(Cloner cloner) {
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82 | return new MultiObjectiveTestFunctionProblem(this, cloner);
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83 | }
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84 |
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85 | public MultiObjectiveTestFunctionProblem() : base() {
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86 | Parameters.Add(new FixedValueParameter<IntValue>("ProblemSize", "The dimensionality of the problem instance (number of variables in the function).", new IntValue(2)));
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87 | Parameters.Add(new FixedValueParameter<IntValue>("Objectives", "The dimensionality of the solution vector (number of objectives).", new IntValue(2)));
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88 | Parameters.Add(new ValueParameter<DoubleMatrix>("Bounds", "The bounds of the solution given as either one line for all variables or a line for each variable. The first column specifies lower bound, the second upper bound.", new DoubleMatrix(new double[,] { { -4, 4 } })));
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89 | Parameters.Add(new ValueParameter<IMultiObjectiveTestFunction>("TestFunction", "The function that is to be optimized.", new Fonseca()));
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90 |
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91 | Encoding.LengthParameter = ProblemSizeParameter;
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92 | Encoding.BoundsParameter = BoundsParameter;
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93 | BestKnownFrontParameter.Hidden = true;
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94 |
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95 | UpdateParameterValues();
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96 | InitializeOperators();
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97 | RegisterEventHandlers();
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98 | }
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99 |
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100 | private void RegisterEventHandlers() {
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101 | TestFunctionParameter.ValueChanged += TestFunctionParameterOnValueChanged;
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102 | ProblemSizeParameter.Value.ValueChanged += ProblemSizeOnValueChanged;
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103 | ObjectivesParameter.Value.ValueChanged += ObjectivesOnValueChanged;
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104 | }
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105 |
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106 |
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107 | public override void Analyze(RealVector[] solutions, double[][] qualities, ResultCollection results, IRandom random) {
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108 | base.Analyze(solutions, qualities, results, random);
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109 | if (results.ContainsKey("Pareto Front"))
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110 | ((DoubleMatrix)results["Pareto Front"].Value).SortableView = true;
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111 | }
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112 |
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113 | /// <summary>
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114 | /// Checks whether a given solution violates the contraints of this function.
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115 | /// </summary>
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116 | /// <param name="individual"></param>
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117 | /// <returns>a double array that holds the distances that describe how much every contraint is violated (0 is not violated). If the current TestFunction does not have constraints an array of length 0 is returned</returns>
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118 | public double[] CheckContraints(RealVector individual) {
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119 | var constrainedTestFunction = (IConstrainedTestFunction)TestFunction;
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120 | return constrainedTestFunction != null ? constrainedTestFunction.CheckConstraints(individual, Objectives) : new double[0];
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121 | }
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122 |
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123 | public override double[] Evaluate(RealVector solution, IRandom random) {
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124 | return TestFunction.Evaluate(solution, Objectives);
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125 | }
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126 |
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127 |
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128 | public void Load(MOTFData data) {
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129 | TestFunction = data.TestFunction;
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130 | }
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131 |
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132 | #region Events
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133 | private void UpdateParameterValues() {
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134 | Maximization = new BoolArray(TestFunction.Maximization(Objectives));
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135 |
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136 | Parameters.Remove(BestKnownFrontParameterName);
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137 | var front = TestFunction.OptimalParetoFront(Objectives);
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138 | var bkf = front != null ? (DoubleMatrix)Utilities.ToMatrix(front).AsReadOnly() : null;
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139 | Parameters.Add(new FixedValueParameter<DoubleMatrix>(BestKnownFrontParameterName, "A double matrix representing the best known qualities for this problem (aka points on the Pareto front). Points are to be given in a row-wise fashion.", bkf));
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140 |
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141 | Parameters.Remove(ReferencePointParameterName);
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142 | Parameters.Add(new FixedValueParameter<DoubleArray>(ReferencePointParameterName, "The reference point for hypervolume calculations on this problem", new DoubleArray(TestFunction.ReferencePoint(Objectives))));
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143 |
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144 | BoundsParameter.Value = new DoubleMatrix(TestFunction.Bounds(Objectives));
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145 | }
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146 |
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147 | protected override void OnEncodingChanged() {
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148 | base.OnEncodingChanged();
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149 | UpdateParameterValues();
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150 | }
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151 |
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152 | protected override void OnEvaluatorChanged() {
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153 | base.OnEvaluatorChanged();
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154 | UpdateParameterValues();
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155 | }
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156 |
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157 | private void TestFunctionParameterOnValueChanged(object sender, EventArgs eventArgs) {
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158 | ProblemSize = Math.Max(TestFunction.MinimumSolutionLength, Math.Min(ProblemSize, TestFunction.MaximumSolutionLength));
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159 | Objectives = Math.Max(TestFunction.MinimumObjectives, Math.Min(Objectives, TestFunction.MaximumObjectives));
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160 | Parameters.Remove(ReferencePointParameterName);
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161 | Parameters.Add(new FixedValueParameter<DoubleArray>(ReferencePointParameterName, "The reference point for hypervolume calculations on this problem", new DoubleArray(TestFunction.ReferencePoint(Objectives))));
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162 | UpdateParameterValues();
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163 | OnReset();
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164 | }
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165 |
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166 | private void ProblemSizeOnValueChanged(object sender, EventArgs eventArgs) {
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167 | ProblemSize = Math.Min(TestFunction.MaximumSolutionLength, Math.Max(TestFunction.MinimumSolutionLength, ProblemSize));
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168 | UpdateParameterValues();
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169 | }
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170 |
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171 | private void ObjectivesOnValueChanged(object sender, EventArgs eventArgs) {
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172 | Objectives = Math.Min(TestFunction.MaximumObjectives, Math.Max(TestFunction.MinimumObjectives, Objectives));
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173 | UpdateParameterValues();
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174 | }
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175 | #endregion
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176 |
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177 | #region Helpers
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178 | private void InitializeOperators() {
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179 | Operators.Add(new CrowdingAnalyzer());
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180 | Operators.Add(new GenerationalDistanceAnalyzer());
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181 | Operators.Add(new InvertedGenerationalDistanceAnalyzer());
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182 | Operators.Add(new HypervolumeAnalyzer());
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183 | Operators.Add(new SpacingAnalyzer());
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184 | Operators.Add(new TimelineAnalyzer());
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185 | }
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186 | #endregion
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187 | }
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188 | } |
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