[4012] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[15973] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[4012] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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[4017] | 23 | using System.Linq;
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[4068] | 24 | using HeuristicLab.Analysis;
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[4012] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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[5356] | 28 | using HeuristicLab.Operators;
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[4012] | 29 | using HeuristicLab.Optimization;
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[4068] | 30 | using HeuristicLab.Optimization.Operators;
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[4012] | 31 | using HeuristicLab.Parameters;
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| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[4068] | 33 | using HeuristicLab.PluginInfrastructure;
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[4017] | 34 | using HeuristicLab.Random;
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[4012] | 35 |
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| 36 | namespace HeuristicLab.Algorithms.NSGA2 {
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| 37 | /// <summary>
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| 38 | /// The Nondominated Sorting Genetic Algorithm II was introduced in Deb et al. 2002. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), pp. 182-197.
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| 39 | /// </summary>
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[4017] | 40 | [Item("NSGA-II", "The Nondominated Sorting Genetic Algorithm II was introduced in Deb et al. 2002. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), pp. 182-197.")]
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[15973] | 41 | [Creatable(CreatableAttribute.Categories.PopulationBasedAlgorithms, Priority = 135)]
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[4012] | 42 | [StorableClass]
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[5809] | 43 | public class NSGA2 : HeuristicOptimizationEngineAlgorithm, IStorableContent {
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[5366] | 44 | public string Filename { get; set; }
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| 45 |
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[4012] | 46 | #region Problem Properties
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| 47 | public override Type ProblemType {
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[5809] | 48 | get { return typeof(IMultiObjectiveHeuristicOptimizationProblem); }
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[4012] | 49 | }
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[5809] | 50 | public new IMultiObjectiveHeuristicOptimizationProblem Problem {
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| 51 | get { return (IMultiObjectiveHeuristicOptimizationProblem)base.Problem; }
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[4012] | 52 | set { base.Problem = value; }
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| 53 | }
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| 54 | #endregion
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| 55 |
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| 56 | #region Parameter Properties
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[4017] | 57 | private ValueParameter<IntValue> SeedParameter {
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| 58 | get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
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[4012] | 59 | }
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[4017] | 60 | private ValueParameter<BoolValue> SetSeedRandomlyParameter {
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| 61 | get { return (ValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
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| 62 | }
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| 63 | private ValueParameter<IntValue> PopulationSizeParameter {
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| 64 | get { return (ValueParameter<IntValue>)Parameters["PopulationSize"]; }
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| 65 | }
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[8121] | 66 | public IConstrainedValueParameter<ISelector> SelectorParameter {
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| 67 | get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
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[4017] | 68 | }
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| 69 | private ValueParameter<PercentValue> CrossoverProbabilityParameter {
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| 70 | get { return (ValueParameter<PercentValue>)Parameters["CrossoverProbability"]; }
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| 71 | }
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[8121] | 72 | public IConstrainedValueParameter<ICrossover> CrossoverParameter {
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| 73 | get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
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[4017] | 74 | }
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| 75 | private ValueParameter<PercentValue> MutationProbabilityParameter {
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| 76 | get { return (ValueParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 77 | }
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[8121] | 78 | public IConstrainedValueParameter<IManipulator> MutatorParameter {
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| 79 | get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
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[4017] | 80 | }
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| 81 | private ValueParameter<MultiAnalyzer> AnalyzerParameter {
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| 82 | get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
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| 83 | }
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| 84 | private ValueParameter<IntValue> MaximumGenerationsParameter {
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| 85 | get { return (ValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 86 | }
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[4514] | 87 | private ValueParameter<IntValue> SelectedParentsParameter {
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| 88 | get { return (ValueParameter<IntValue>)Parameters["SelectedParents"]; }
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| 89 | }
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[12123] | 90 |
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| 91 | private IFixedValueParameter<BoolValue> DominateOnEqualQualitiesParameter {
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| 92 | get { return (IFixedValueParameter<BoolValue>)Parameters["DominateOnEqualQualities"]; }
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| 93 | }
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[4012] | 94 | #endregion
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| 95 |
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| 96 | #region Properties
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[4017] | 97 | public IntValue Seed {
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| 98 | get { return SeedParameter.Value; }
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| 99 | set { SeedParameter.Value = value; }
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| 100 | }
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| 101 | public BoolValue SetSeedRandomly {
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| 102 | get { return SetSeedRandomlyParameter.Value; }
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| 103 | set { SetSeedRandomlyParameter.Value = value; }
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| 104 | }
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| 105 | public IntValue PopulationSize {
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| 106 | get { return PopulationSizeParameter.Value; }
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| 107 | set { PopulationSizeParameter.Value = value; }
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| 108 | }
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| 109 | public ISelector Selector {
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| 110 | get { return SelectorParameter.Value; }
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| 111 | set { SelectorParameter.Value = value; }
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| 112 | }
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| 113 | public PercentValue CrossoverProbability {
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| 114 | get { return CrossoverProbabilityParameter.Value; }
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| 115 | set { CrossoverProbabilityParameter.Value = value; }
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| 116 | }
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| 117 | public ICrossover Crossover {
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| 118 | get { return CrossoverParameter.Value; }
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| 119 | set { CrossoverParameter.Value = value; }
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| 120 | }
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| 121 | public PercentValue MutationProbability {
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| 122 | get { return MutationProbabilityParameter.Value; }
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| 123 | set { MutationProbabilityParameter.Value = value; }
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| 124 | }
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| 125 | public IManipulator Mutator {
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| 126 | get { return MutatorParameter.Value; }
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| 127 | set { MutatorParameter.Value = value; }
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| 128 | }
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| 129 | public MultiAnalyzer Analyzer {
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| 130 | get { return AnalyzerParameter.Value; }
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| 131 | set { AnalyzerParameter.Value = value; }
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| 132 | }
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| 133 | public IntValue MaximumGenerations {
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| 134 | get { return MaximumGenerationsParameter.Value; }
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| 135 | set { MaximumGenerationsParameter.Value = value; }
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| 136 | }
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[4514] | 137 | public IntValue SelectedParents {
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| 138 | get { return SelectedParentsParameter.Value; }
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| 139 | set { SelectedParentsParameter.Value = value; }
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| 140 | }
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[12123] | 141 | public bool DominateOnEqualQualities {
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| 142 | get { return DominateOnEqualQualitiesParameter.Value.Value; }
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| 143 | set { DominateOnEqualQualitiesParameter.Value.Value = value; }
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| 144 | }
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| 145 |
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[4017] | 146 | private RandomCreator RandomCreator {
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| 147 | get { return (RandomCreator)OperatorGraph.InitialOperator; }
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| 148 | }
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| 149 | private SolutionsCreator SolutionsCreator {
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| 150 | get { return (SolutionsCreator)RandomCreator.Successor; }
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| 151 | }
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[4045] | 152 | private RankAndCrowdingSorter RankAndCrowdingSorter {
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[5356] | 153 | get { return (RankAndCrowdingSorter)((SubScopesCounter)SolutionsCreator.Successor).Successor; }
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[4045] | 154 | }
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[4017] | 155 | private NSGA2MainLoop MainLoop {
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[5366] | 156 | get { return FindMainLoop(RankAndCrowdingSorter.Successor); }
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[4017] | 157 | }
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[4012] | 158 | #endregion
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| 159 |
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[4086] | 160 | [Storable]
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[5143] | 161 | private RankBasedParetoFrontAnalyzer paretoFrontAnalyzer;
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[4086] | 162 |
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[4012] | 163 | [StorableConstructor]
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[4902] | 164 | protected NSGA2(bool deserializing) : base(deserializing) { }
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[5356] | 165 | protected NSGA2(NSGA2 original, Cloner cloner)
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| 166 | : base(original, cloner) {
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[5143] | 167 | paretoFrontAnalyzer = (RankBasedParetoFrontAnalyzer)cloner.Clone(original.paretoFrontAnalyzer);
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[7351] | 168 | AfterDeserialization();
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[4902] | 169 | }
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[4012] | 170 | public NSGA2() {
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[4017] | 171 | Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
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| 172 | Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
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| 173 | Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
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| 174 | Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
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[4045] | 175 | Parameters.Add(new ValueParameter<PercentValue>("CrossoverProbability", "The probability that the crossover operator is applied on two parents.", new PercentValue(0.9)));
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[4017] | 176 | Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
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| 177 | Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
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[15973] | 178 | Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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[4017] | 179 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
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| 180 | Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed.", new IntValue(1000)));
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[4514] | 181 | Parameters.Add(new ValueParameter<IntValue>("SelectedParents", "Each two parents form a new child, typically this value should be twice the population size, but because the NSGA-II is maximally elitist it can be any multiple of 2 greater than 0.", new IntValue(200)));
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[12123] | 182 | Parameters.Add(new FixedValueParameter<BoolValue>("DominateOnEqualQualities", "Flag which determines wether solutions with equal quality values should be treated as dominated.", new BoolValue(false)));
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[4017] | 183 |
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| 184 | RandomCreator randomCreator = new RandomCreator();
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| 185 | SolutionsCreator solutionsCreator = new SolutionsCreator();
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[5356] | 186 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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[4045] | 187 | RankAndCrowdingSorter rankAndCrowdingSorter = new RankAndCrowdingSorter();
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[5356] | 188 | ResultsCollector resultsCollector = new ResultsCollector();
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[4017] | 189 | NSGA2MainLoop mainLoop = new NSGA2MainLoop();
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[5356] | 190 |
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[4017] | 191 | OperatorGraph.InitialOperator = randomCreator;
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| 192 |
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| 193 | randomCreator.RandomParameter.ActualName = "Random";
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| 194 | randomCreator.SeedParameter.ActualName = SeedParameter.Name;
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| 195 | randomCreator.SeedParameter.Value = null;
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| 196 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
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| 197 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 198 | randomCreator.Successor = solutionsCreator;
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| 199 |
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| 200 | solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
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[5356] | 201 | solutionsCreator.Successor = subScopesCounter;
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[4017] | 202 |
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[5356] | 203 | subScopesCounter.Name = "Initialize EvaluatedSolutions";
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| 204 | subScopesCounter.ValueParameter.ActualName = "EvaluatedSolutions";
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| 205 | subScopesCounter.Successor = rankAndCrowdingSorter;
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| 206 |
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[12123] | 207 | rankAndCrowdingSorter.DominateOnEqualQualitiesParameter.ActualName = DominateOnEqualQualitiesParameter.Name;
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[4045] | 208 | rankAndCrowdingSorter.CrowdingDistanceParameter.ActualName = "CrowdingDistance";
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| 209 | rankAndCrowdingSorter.RankParameter.ActualName = "Rank";
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[5356] | 210 | rankAndCrowdingSorter.Successor = resultsCollector;
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[4045] | 211 |
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[5356] | 212 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
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| 213 | resultsCollector.ResultsParameter.ActualName = "Results";
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| 214 | resultsCollector.Successor = mainLoop;
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| 215 |
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[4045] | 216 | mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
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[4017] | 217 | mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
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| 218 | mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
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| 219 | mainLoop.CrossoverProbabilityParameter.ActualName = CrossoverProbabilityParameter.Name;
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| 220 | mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
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| 221 | mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
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| 222 | mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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| 223 | mainLoop.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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| 224 | mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
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| 225 | mainLoop.ResultsParameter.ActualName = "Results";
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[5356] | 226 | mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
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[4017] | 227 |
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[4045] | 228 | foreach (ISelector selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(x => !(x is ISingleObjectiveSelector)).OrderBy(x => x.Name))
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[4017] | 229 | SelectorParameter.ValidValues.Add(selector);
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[4045] | 230 | ISelector tournamentSelector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("CrowdedTournamentSelector"));
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| 231 | if (tournamentSelector != null) SelectorParameter.Value = tournamentSelector;
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[4017] | 232 |
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[4045] | 233 | ParameterizeSelectors();
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| 234 |
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[5143] | 235 | paretoFrontAnalyzer = new RankBasedParetoFrontAnalyzer();
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| 236 | paretoFrontAnalyzer.RankParameter.ActualName = "Rank";
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| 237 | paretoFrontAnalyzer.RankParameter.Depth = 1;
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| 238 | paretoFrontAnalyzer.ResultsParameter.ActualName = "Results";
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[4086] | 239 | ParameterizeAnalyzers();
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| 240 | UpdateAnalyzers();
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| 241 |
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[7351] | 242 | AfterDeserialization();
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[4012] | 243 | }
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| 244 |
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| 245 | public override IDeepCloneable Clone(Cloner cloner) {
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[5356] | 246 | return new NSGA2(this, cloner);
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[4012] | 247 | }
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[4017] | 248 |
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[7209] | 249 | public override void Prepare() {
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| 250 | if (Problem != null) base.Prepare();
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| 251 | }
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| 252 |
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[4017] | 253 | #region Events
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| 254 | protected override void OnProblemChanged() {
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[4045] | 255 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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| 256 | ParameterizeStochasticOperator(Problem.Evaluator);
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[7999] | 257 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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[4045] | 258 | ParameterizeSolutionsCreator();
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[4067] | 259 | ParameterizeRankAndCrowdingSorter();
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[4045] | 260 | ParameterizeMainLoop();
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| 261 | ParameterizeSelectors();
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| 262 | ParameterizeAnalyzers();
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| 263 | ParameterizeIterationBasedOperators();
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| 264 | UpdateCrossovers();
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| 265 | UpdateMutators();
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| 266 | UpdateAnalyzers();
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| 267 | Problem.Evaluator.QualitiesParameter.ActualNameChanged += new EventHandler(Evaluator_QualitiesParameter_ActualNameChanged);
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[4017] | 268 | base.OnProblemChanged();
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| 269 | }
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| 270 | protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
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[4045] | 271 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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| 272 | ParameterizeSolutionsCreator();
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[4017] | 273 | base.Problem_SolutionCreatorChanged(sender, e);
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| 274 | }
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| 275 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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[4045] | 276 | ParameterizeStochasticOperator(Problem.Evaluator);
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| 277 | ParameterizeSolutionsCreator();
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[4067] | 278 | ParameterizeRankAndCrowdingSorter();
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[4045] | 279 | ParameterizeMainLoop();
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| 280 | ParameterizeSelectors();
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| 281 | ParameterizeAnalyzers();
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[4017] | 282 | Problem.Evaluator.QualitiesParameter.ActualNameChanged += new EventHandler(Evaluator_QualitiesParameter_ActualNameChanged);
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| 283 | base.Problem_EvaluatorChanged(sender, e);
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| 284 | }
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| 285 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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[7999] | 286 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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[4045] | 287 | ParameterizeIterationBasedOperators();
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| 288 | UpdateCrossovers();
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| 289 | UpdateMutators();
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| 290 | UpdateAnalyzers();
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[4017] | 291 | base.Problem_OperatorsChanged(sender, e);
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| 292 | }
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| 293 | protected override void Problem_Reset(object sender, EventArgs e) {
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| 294 | base.Problem_Reset(sender, e);
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| 295 | }
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| 296 | private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
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| 297 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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[4045] | 298 | ParameterizeSelectors();
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[4017] | 299 | }
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| 300 | private void PopulationSize_ValueChanged(object sender, EventArgs e) {
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[4045] | 301 | ParameterizeSelectors();
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[4017] | 302 | }
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| 303 | private void Evaluator_QualitiesParameter_ActualNameChanged(object sender, EventArgs e) {
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[4067] | 304 | ParameterizeRankAndCrowdingSorter();
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[4045] | 305 | ParameterizeMainLoop();
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| 306 | ParameterizeSelectors();
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| 307 | ParameterizeAnalyzers();
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[4017] | 308 | }
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[4514] | 309 | private void SelectedParentsParameter_ValueChanged(object sender, EventArgs e) {
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| 310 | SelectedParents.ValueChanged += new EventHandler(SelectedParents_ValueChanged);
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| 311 | SelectedParents_ValueChanged(null, EventArgs.Empty);
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| 312 | }
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| 313 | private void SelectedParents_ValueChanged(object sender, EventArgs e) {
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| 314 | if (SelectedParents.Value < 2) SelectedParents.Value = 2;
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| 315 | else if (SelectedParents.Value % 2 != 0) {
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| 316 | SelectedParents.Value = SelectedParents.Value + 1;
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| 317 | }
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| 318 | }
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[4017] | 319 | #endregion
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| 320 |
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| 321 | #region Helpers
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| 322 | [StorableHook(HookType.AfterDeserialization)]
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[7351] | 323 | private void AfterDeserialization() {
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[12123] | 324 | // BackwardsCompatibility3.3
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| 325 | #region Backwards compatible code, remove with 3.4
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| 326 | if (!Parameters.ContainsKey("DominateOnEqualQualities"))
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| 327 | Parameters.Add(new FixedValueParameter<BoolValue>("DominateOnEqualQualities", "Flag which determines wether solutions with equal quality values should be treated as dominated.", new BoolValue(false)));
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[15973] | 328 | var optionalMutatorParameter = MutatorParameter as OptionalConstrainedValueParameter<IManipulator>;
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| 329 | if (optionalMutatorParameter != null) {
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| 330 | Parameters.Remove(optionalMutatorParameter);
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| 331 | Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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| 332 | foreach (var m in optionalMutatorParameter.ValidValues)
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| 333 | MutatorParameter.ValidValues.Add(m);
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| 334 | if (optionalMutatorParameter.Value == null) MutationProbability.Value = 0; // to guarantee that the old configuration results in the same behavior
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| 335 | else Mutator = optionalMutatorParameter.Value;
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| 336 | optionalMutatorParameter.ValidValues.Clear(); // to avoid dangling references to the old parameter its valid values are cleared
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| 337 | }
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[12123] | 338 | #endregion
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| 339 |
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[4017] | 340 | PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
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| 341 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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[4514] | 342 | SelectedParentsParameter.ValueChanged += new EventHandler(SelectedParentsParameter_ValueChanged);
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| 343 | SelectedParents.ValueChanged += new EventHandler(SelectedParents_ValueChanged);
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[4017] | 344 | if (Problem != null) {
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| 345 | Problem.Evaluator.QualitiesParameter.ActualNameChanged += new EventHandler(Evaluator_QualitiesParameter_ActualNameChanged);
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| 346 | }
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| 347 | }
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[4045] | 348 | private void ParameterizeSolutionsCreator() {
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| 349 | SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 350 | SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
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| 351 | }
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[4067] | 352 | private void ParameterizeRankAndCrowdingSorter() {
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| 353 | RankAndCrowdingSorter.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 354 | RankAndCrowdingSorter.QualitiesParameter.ActualName = Problem.Evaluator.QualitiesParameter.ActualName;
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| 355 | }
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[4045] | 356 | private void ParameterizeMainLoop() {
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| 357 | MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 358 | MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 359 | MainLoop.QualitiesParameter.ActualName = Problem.Evaluator.QualitiesParameter.ActualName;
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| 360 | }
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| 361 | private void ParameterizeStochasticOperator(IOperator op) {
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| 362 | if (op is IStochasticOperator)
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| 363 | ((IStochasticOperator)op).RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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| 364 | }
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| 365 | private void ParameterizeSelectors() {
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| 366 | foreach (ISelector selector in SelectorParameter.ValidValues) {
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| 367 | selector.CopySelected = new BoolValue(true);
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[4514] | 368 | selector.NumberOfSelectedSubScopesParameter.ActualName = SelectedParentsParameter.Name;
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[4045] | 369 | ParameterizeStochasticOperator(selector);
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| 370 | }
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| 371 | if (Problem != null) {
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| 372 | foreach (IMultiObjectiveSelector selector in SelectorParameter.ValidValues.OfType<IMultiObjectiveSelector>()) {
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| 373 | selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 374 | selector.QualitiesParameter.ActualName = Problem.Evaluator.QualitiesParameter.ActualName;
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| 375 | }
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| 376 | }
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| 377 | }
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| 378 | private void ParameterizeAnalyzers() {
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[4086] | 379 | if (Problem != null) {
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[5143] | 380 | paretoFrontAnalyzer.QualitiesParameter.ActualName = Problem.Evaluator.QualitiesParameter.ActualName;
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| 381 | paretoFrontAnalyzer.QualitiesParameter.Depth = 1;
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[4086] | 382 | }
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[4045] | 383 | }
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| 384 | private void ParameterizeIterationBasedOperators() {
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| 385 | if (Problem != null) {
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| 386 | foreach (IIterationBasedOperator op in Problem.Operators.OfType<IIterationBasedOperator>()) {
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| 387 | op.IterationsParameter.ActualName = "Generations";
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| 388 | op.MaximumIterationsParameter.ActualName = "MaximumGenerations";
|
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| 389 | }
|
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| 390 | }
|
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| 391 | }
|
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| 392 | private void UpdateCrossovers() {
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| 393 | ICrossover oldCrossover = CrossoverParameter.Value;
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[7511] | 394 | ICrossover defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
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[4045] | 395 | CrossoverParameter.ValidValues.Clear();
|
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| 396 | foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
|
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| 397 | CrossoverParameter.ValidValues.Add(crossover);
|
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| 398 | if (oldCrossover != null) {
|
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| 399 | ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
|
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| 400 | if (crossover != null) CrossoverParameter.Value = crossover;
|
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[7511] | 401 | else oldCrossover = null;
|
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[4045] | 402 | }
|
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[7511] | 403 | if (oldCrossover == null && defaultCrossover != null)
|
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| 404 | CrossoverParameter.Value = defaultCrossover;
|
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[4045] | 405 | }
|
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| 406 | private void UpdateMutators() {
|
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| 407 | IManipulator oldMutator = MutatorParameter.Value;
|
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| 408 | MutatorParameter.ValidValues.Clear();
|
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[15973] | 409 | IManipulator defaultMutator = Problem.Operators.OfType<IManipulator>().FirstOrDefault();
|
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[4045] | 410 | foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
|
---|
| 411 | MutatorParameter.ValidValues.Add(mutator);
|
---|
| 412 | if (oldMutator != null) {
|
---|
| 413 | IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
|
---|
| 414 | if (mutator != null) MutatorParameter.Value = mutator;
|
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[15973] | 415 | else oldMutator = null;
|
---|
[4045] | 416 | }
|
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[15973] | 417 | if (oldMutator == null && defaultMutator != null)
|
---|
| 418 | MutatorParameter.Value = defaultMutator;
|
---|
[4045] | 419 | }
|
---|
| 420 | private void UpdateAnalyzers() {
|
---|
| 421 | Analyzer.Operators.Clear();
|
---|
| 422 | if (Problem != null) {
|
---|
| 423 | foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>()) {
|
---|
| 424 | foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
|
---|
| 425 | param.Depth = 1;
|
---|
[7172] | 426 | Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
|
---|
[4045] | 427 | }
|
---|
| 428 | }
|
---|
[7172] | 429 | Analyzer.Operators.Add(paretoFrontAnalyzer, paretoFrontAnalyzer.EnabledByDefault);
|
---|
[4045] | 430 | }
|
---|
[5366] | 431 | private NSGA2MainLoop FindMainLoop(IOperator start) {
|
---|
| 432 | IOperator mainLoop = start;
|
---|
| 433 | while (mainLoop != null && !(mainLoop is NSGA2MainLoop))
|
---|
| 434 | mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
|
---|
| 435 | if (mainLoop == null) return null;
|
---|
| 436 | else return (NSGA2MainLoop)mainLoop;
|
---|
| 437 | }
|
---|
[4017] | 438 | #endregion
|
---|
[4012] | 439 | }
|
---|
| 440 | }
|
---|