[8313] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8313] | 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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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Analysis;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Operators;
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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Optimization.Operators;
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| 31 | using HeuristicLab.Parameters;
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| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 33 | using HeuristicLab.PluginInfrastructure;
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| 34 | using HeuristicLab.Random;
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| 35 |
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| 36 | namespace HeuristicLab.Algorithms.RAPGA {
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| 37 | /// <summary>
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| 38 | /// A relevant alleles preserving genetic algorithm.
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| 39 | /// </summary>
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[8629] | 40 | [Item("RAPGA", "A relevant alleles preserving genetic algorithm (Affenzeller, M. et al. 2007. Self-adaptive population size adjustment for genetic algorithms. Proceedings of Computer Aided Systems Theory: EuroCAST 2007, Lecture Notes in Computer Science, pp 820–828. Springer).")]
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[8313] | 41 | [Creatable("Algorithms")]
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| 42 | [StorableClass]
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| 43 | public sealed class RAPGA : HeuristicOptimizationEngineAlgorithm, IStorableContent {
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| 44 | public string Filename { get; set; }
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| 45 |
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| 46 | #region Problem Properties
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| 47 | public override Type ProblemType {
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| 48 | get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
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| 49 | }
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| 50 | public new ISingleObjectiveHeuristicOptimizationProblem Problem {
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| 51 | get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
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| 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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| 57 | private ValueParameter<IntValue> SeedParameter {
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| 58 | get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
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| 59 | }
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| 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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[8330] | 66 | private IValueParameter<IntValue> MinimumPopulationSizeParameter {
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| 67 | get { return (IValueParameter<IntValue>)Parameters["MinimumPopulationSize"]; }
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[8349] | 68 | }
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[8330] | 69 | private IValueParameter<IntValue> MaximumPopulationSizeParameter {
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[8349] | 70 | get { return (IValueParameter<IntValue>)Parameters["MaximumPopulationSize"]; }
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[8330] | 71 | }
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| 72 | private IValueParameter<DoubleValue> ComparisonFactorParameter {
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| 73 | get { return (IValueParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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| 74 | }
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| 75 | private IValueParameter<IntValue> EffortParameter {
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| 76 | get { return (IValueParameter<IntValue>)Parameters["Effort"]; }
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| 77 | }
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[8377] | 78 | private IValueParameter<IntValue> BatchSizeParameter {
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| 79 | get { return (IValueParameter<IntValue>)Parameters["BatchSize"]; }
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| 80 | }
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[8313] | 81 | public IConstrainedValueParameter<ISelector> SelectorParameter {
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| 82 | get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
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| 83 | }
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| 84 | public IConstrainedValueParameter<ICrossover> CrossoverParameter {
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| 85 | get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
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| 86 | }
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| 87 | private ValueParameter<PercentValue> MutationProbabilityParameter {
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| 88 | get { return (ValueParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 89 | }
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| 90 | public IConstrainedValueParameter<IManipulator> MutatorParameter {
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| 91 | get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
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| 92 | }
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| 93 | private ValueParameter<IntValue> ElitesParameter {
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| 94 | get { return (ValueParameter<IntValue>)Parameters["Elites"]; }
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| 95 | }
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[9569] | 96 | private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
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| 97 | get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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| 98 | }
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[8313] | 99 | private ValueParameter<MultiAnalyzer> AnalyzerParameter {
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| 100 | get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
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| 101 | }
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| 102 | private ValueParameter<IntValue> MaximumGenerationsParameter {
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| 103 | get { return (ValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 104 | }
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[8407] | 105 | public IConstrainedValueParameter<ISingleObjectiveSolutionSimilarityCalculator> SimilarityCalculatorParameter {
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| 106 | get { return (IConstrainedValueParameter<ISingleObjectiveSolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
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[8349] | 107 | }
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[8313] | 108 | #endregion
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| 109 |
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| 110 | #region Properties
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| 111 | public IntValue Seed {
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| 112 | get { return SeedParameter.Value; }
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| 113 | set { SeedParameter.Value = value; }
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| 114 | }
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| 115 | public BoolValue SetSeedRandomly {
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| 116 | get { return SetSeedRandomlyParameter.Value; }
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| 117 | set { SetSeedRandomlyParameter.Value = value; }
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| 118 | }
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| 119 | public IntValue PopulationSize {
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| 120 | get { return PopulationSizeParameter.Value; }
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| 121 | set { PopulationSizeParameter.Value = value; }
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| 122 | }
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[8330] | 123 | public IntValue MinimumPopulationSize {
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| 124 | get { return MinimumPopulationSizeParameter.Value; }
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| 125 | set { MinimumPopulationSizeParameter.Value = value; }
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| 126 | }
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| 127 | public IntValue MaximumPopulationSize {
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| 128 | get { return MaximumPopulationSizeParameter.Value; }
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| 129 | set { MaximumPopulationSizeParameter.Value = value; }
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| 130 | }
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| 131 | public DoubleValue ComparisonFactor {
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| 132 | get { return ComparisonFactorParameter.Value; }
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| 133 | set { ComparisonFactorParameter.Value = value; }
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| 134 | }
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| 135 | public IntValue Effort {
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| 136 | get { return EffortParameter.Value; }
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| 137 | set { EffortParameter.Value = value; }
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| 138 | }
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[8377] | 139 | public IntValue BatchSize {
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| 140 | get { return BatchSizeParameter.Value; }
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| 141 | set { BatchSizeParameter.Value = value; }
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| 142 | }
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[8313] | 143 | public ISelector Selector {
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| 144 | get { return SelectorParameter.Value; }
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| 145 | set { SelectorParameter.Value = value; }
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| 146 | }
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| 147 | public ICrossover Crossover {
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| 148 | get { return CrossoverParameter.Value; }
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| 149 | set { CrossoverParameter.Value = value; }
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| 150 | }
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| 151 | public PercentValue MutationProbability {
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| 152 | get { return MutationProbabilityParameter.Value; }
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| 153 | set { MutationProbabilityParameter.Value = value; }
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| 154 | }
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| 155 | public IManipulator Mutator {
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| 156 | get { return MutatorParameter.Value; }
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| 157 | set { MutatorParameter.Value = value; }
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| 158 | }
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| 159 | public IntValue Elites {
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| 160 | get { return ElitesParameter.Value; }
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| 161 | set { ElitesParameter.Value = value; }
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| 162 | }
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[9569] | 163 | public bool ReevaluteElites {
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| 164 | get { return ReevaluateElitesParameter.Value.Value; }
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| 165 | set { ReevaluateElitesParameter.Value.Value = value; }
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| 166 | }
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[8313] | 167 | public MultiAnalyzer Analyzer {
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| 168 | get { return AnalyzerParameter.Value; }
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| 169 | set { AnalyzerParameter.Value = value; }
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| 170 | }
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| 171 | public IntValue MaximumGenerations {
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| 172 | get { return MaximumGenerationsParameter.Value; }
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| 173 | set { MaximumGenerationsParameter.Value = value; }
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| 174 | }
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[8407] | 175 | public ISingleObjectiveSolutionSimilarityCalculator SimilarityCalculator {
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[8349] | 176 | get { return SimilarityCalculatorParameter.Value; }
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| 177 | set { SimilarityCalculatorParameter.Value = value; }
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| 178 | }
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[8313] | 179 | private RandomCreator RandomCreator {
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| 180 | get { return (RandomCreator)OperatorGraph.InitialOperator; }
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| 181 | }
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| 182 | private SolutionsCreator SolutionsCreator {
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| 183 | get { return (SolutionsCreator)RandomCreator.Successor; }
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| 184 | }
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| 185 | private RAPGAMainLoop RAPGAMainLoop {
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| 186 | get { return FindMainLoop(SolutionsCreator.Successor); }
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| 187 | }
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| 188 | [Storable]
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| 189 | private BestAverageWorstQualityAnalyzer qualityAnalyzer;
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[8377] | 190 | [Storable]
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| 191 | private PopulationSizeAnalyzer populationSizeAnalyzer;
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[8378] | 192 | [Storable]
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| 193 | private OffspringSuccessAnalyzer offspringSuccessAnalyzer;
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[8385] | 194 | [Storable]
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| 195 | private SelectionPressureAnalyzer selectionPressureAnalyzer;
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[8313] | 196 | #endregion
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| 197 |
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| 198 | [StorableConstructor]
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| 199 | private RAPGA(bool deserializing) : base(deserializing) { }
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| 200 | [StorableHook(HookType.AfterDeserialization)]
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[9569] | 201 | private void AfterDeserialization() {
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[9592] | 202 | // BackwardsCompatibility3.3
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[9591] | 203 | #region Backwards compatible code, remove with 3.4
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[9569] | 204 | if (!Parameters.ContainsKey("ReevaluateElites")) {
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| 205 | Parameters.Add(new FixedValueParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", (BoolValue)new BoolValue(false).AsReadOnly()) { Hidden = true });
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| 206 | }
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[9591] | 207 | #endregion
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[9569] | 208 | Initialize();
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| 209 | }
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[8313] | 210 | private RAPGA(RAPGA original, Cloner cloner)
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| 211 | : base(original, cloner) {
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| 212 | qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
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[8377] | 213 | populationSizeAnalyzer = cloner.Clone(original.populationSizeAnalyzer);
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[8378] | 214 | offspringSuccessAnalyzer = cloner.Clone(original.offspringSuccessAnalyzer);
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[8385] | 215 | selectionPressureAnalyzer = cloner.Clone(original.selectionPressureAnalyzer);
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[8313] | 216 | Initialize();
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| 217 | }
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| 218 | public RAPGA()
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| 219 | : base() {
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| 220 | 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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| 221 | 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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[8359] | 222 | Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
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[8330] | 223 | Parameters.Add(new ValueParameter<IntValue>("MinimumPopulationSize", "The minimum size of the population of solutions.", new IntValue(2)));
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[8377] | 224 | Parameters.Add(new ValueParameter<IntValue>("MaximumPopulationSize", "The maximum size of the population of solutions.", new IntValue(300)));
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[8330] | 225 | Parameters.Add(new ValueParameter<DoubleValue>("ComparisonFactor", "The comparison factor.", new DoubleValue(0.0)));
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[8377] | 226 | Parameters.Add(new ValueParameter<IntValue>("Effort", "The maximum number of offspring created in each generation.", new IntValue(1000)));
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| 227 | Parameters.Add(new ValueParameter<IntValue>("BatchSize", "The number of children that should be created during one iteration of the offspring creation process.", new IntValue(10)));
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[8313] | 228 | Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
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| 229 | Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
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| 230 | 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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| 231 | Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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| 232 | Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
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[9569] | 233 | Parameters.Add(new FixedValueParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", new BoolValue(false)) { Hidden = true });
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[8313] | 234 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
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| 235 | Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed.", new IntValue(1000)));
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[8407] | 236 | Parameters.Add(new ConstrainedValueParameter<ISingleObjectiveSolutionSimilarityCalculator>("SimilarityCalculator", "The operator used to calculate the similarity between two solutions."));
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[8313] | 237 |
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| 238 | RandomCreator randomCreator = new RandomCreator();
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| 239 | SolutionsCreator solutionsCreator = new SolutionsCreator();
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| 240 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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| 241 | ResultsCollector resultsCollector = new ResultsCollector();
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| 242 | RAPGAMainLoop mainLoop = new RAPGAMainLoop();
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| 243 | OperatorGraph.InitialOperator = randomCreator;
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| 244 |
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| 245 | randomCreator.RandomParameter.ActualName = "Random";
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| 246 | randomCreator.SeedParameter.ActualName = SeedParameter.Name;
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| 247 | randomCreator.SeedParameter.Value = null;
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| 248 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
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| 249 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 250 | randomCreator.Successor = solutionsCreator;
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| 251 |
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| 252 | solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
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| 253 | solutionsCreator.Successor = subScopesCounter;
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| 254 |
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| 255 | subScopesCounter.Name = "Initialize EvaluatedSolutions";
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| 256 | subScopesCounter.ValueParameter.ActualName = "EvaluatedSolutions";
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| 257 | subScopesCounter.Successor = resultsCollector;
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| 258 |
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| 259 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
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| 260 | resultsCollector.ResultsParameter.ActualName = "Results";
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| 261 | resultsCollector.Successor = mainLoop;
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| 262 |
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| 263 | mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
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| 264 | mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
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| 265 | mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
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[9569] | 266 | mainLoop.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
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[8313] | 267 | mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
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| 268 | mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
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| 269 | mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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| 270 | mainLoop.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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| 271 | mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
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| 272 | mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
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| 273 | mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
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| 274 | mainLoop.ResultsParameter.ActualName = "Results";
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| 275 |
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| 276 | foreach (ISelector selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
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| 277 | SelectorParameter.ValidValues.Add(selector);
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| 278 | ISelector proportionalSelector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("ProportionalSelector"));
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| 279 | if (proportionalSelector != null) SelectorParameter.Value = proportionalSelector;
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| 280 | ParameterizeSelectors();
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| 281 |
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| 282 | qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
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[8377] | 283 | populationSizeAnalyzer = new PopulationSizeAnalyzer();
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[8378] | 284 | offspringSuccessAnalyzer = new OffspringSuccessAnalyzer();
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[8385] | 285 | selectionPressureAnalyzer = new SelectionPressureAnalyzer();
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[8313] | 286 | ParameterizeAnalyzers();
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| 287 | UpdateAnalyzers();
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| 288 |
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| 289 | Initialize();
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| 290 | }
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| 291 | public override IDeepCloneable Clone(Cloner cloner) {
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| 292 | return new RAPGA(this, cloner);
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| 293 | }
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| 294 |
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| 295 | public override void Prepare() {
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[8349] | 296 | if (Problem != null && SimilarityCalculator != null) base.Prepare();
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[8313] | 297 | }
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| 298 |
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| 299 | #region Events
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| 300 | protected override void OnProblemChanged() {
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| 301 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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| 302 | ParameterizeStochasticOperator(Problem.Evaluator);
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| 303 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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| 304 | ParameterizeSolutionsCreator();
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| 305 | ParameterizeSelectors();
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| 306 | ParameterizeAnalyzers();
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| 307 | ParameterizeIterationBasedOperators();
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| 308 | UpdateCrossovers();
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| 309 | UpdateMutators();
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| 310 | UpdateAnalyzers();
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[8349] | 311 | UpdateSimilarityCalculators();
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| 312 | ParameterizeRAPGAMainLoop();
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[8313] | 313 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 314 | base.OnProblemChanged();
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| 315 | }
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| 316 |
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| 317 | protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
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| 318 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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| 319 | ParameterizeSolutionsCreator();
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| 320 | base.Problem_SolutionCreatorChanged(sender, e);
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| 321 | }
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| 322 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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| 323 | ParameterizeStochasticOperator(Problem.Evaluator);
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| 324 | ParameterizeSolutionsCreator();
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[8349] | 325 | ParameterizeRAPGAMainLoop();
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[8313] | 326 | ParameterizeSelectors();
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| 327 | ParameterizeAnalyzers();
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| 328 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 329 | base.Problem_EvaluatorChanged(sender, e);
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| 330 | }
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| 331 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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[8349] | 332 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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[8313] | 333 | ParameterizeIterationBasedOperators();
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| 334 | UpdateCrossovers();
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| 335 | UpdateMutators();
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| 336 | UpdateAnalyzers();
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[8349] | 337 | UpdateSimilarityCalculators();
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| 338 | ParameterizeRAPGAMainLoop();
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[8313] | 339 | base.Problem_OperatorsChanged(sender, e);
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| 340 | }
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[8406] | 341 | private void SimilarityCalculatorParameter_ValueChanged(object sender, EventArgs e) {
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| 342 | ParameterizeRAPGAMainLoop();
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| 343 | }
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| 344 | private void BatchSizeParameter_ValueChanged(object sender, EventArgs e) {
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[8377] | 345 | BatchSize.ValueChanged += new EventHandler(BatchSize_ValueChanged);
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[8359] | 346 | ParameterizeSelectors();
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| 347 | }
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[8406] | 348 | private void BatchSize_ValueChanged(object sender, EventArgs e) {
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[8359] | 349 | ParameterizeSelectors();
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| 350 | }
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[8313] | 351 | private void ElitesParameter_ValueChanged(object sender, EventArgs e) {
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| 352 | Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
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| 353 | ParameterizeSelectors();
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| 354 | }
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| 355 | private void Elites_ValueChanged(object sender, EventArgs e) {
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| 356 | ParameterizeSelectors();
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| 357 | }
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| 358 |
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| 359 | private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
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| 360 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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| 361 | ParameterizeSelectors();
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| 362 | }
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| 363 | private void PopulationSize_ValueChanged(object sender, EventArgs e) {
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| 364 | ParameterizeSelectors();
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| 365 | }
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| 366 | private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
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[8349] | 367 | ParameterizeRAPGAMainLoop();
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[8313] | 368 | ParameterizeSelectors();
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| 369 | ParameterizeAnalyzers();
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[8407] | 370 | ParameterizeSimilarityCalculators();
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[8313] | 371 | }
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| 372 | #endregion
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| 373 |
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| 374 | #region Helpers
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| 375 | private void Initialize() {
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| 376 | PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
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| 377 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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| 378 | ElitesParameter.ValueChanged += new EventHandler(ElitesParameter_ValueChanged);
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| 379 | Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
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[8377] | 380 | BatchSizeParameter.ValueChanged += new EventHandler(BatchSizeParameter_ValueChanged);
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| 381 | BatchSize.ValueChanged += new EventHandler(BatchSize_ValueChanged);
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[8406] | 382 | SimilarityCalculatorParameter.ValueChanged += new EventHandler(SimilarityCalculatorParameter_ValueChanged);
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[8313] | 383 | if (Problem != null) {
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| 384 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 385 | }
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| 386 | }
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| 387 |
|
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| 388 | private void ParameterizeSolutionsCreator() {
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| 389 | SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 390 | SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
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| 391 | }
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[8349] | 392 | private void ParameterizeRAPGAMainLoop() {
|
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[8313] | 393 | RAPGAMainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
|
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| 394 | RAPGAMainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 395 | RAPGAMainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
|
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[8349] | 396 | foreach (ISimilarityBasedOperator op in RAPGAMainLoop.OperatorGraph.Operators.OfType<ISimilarityBasedOperator>())
|
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| 397 | op.SimilarityCalculator = SimilarityCalculator;
|
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[8313] | 398 | }
|
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| 399 | private void ParameterizeStochasticOperator(IOperator op) {
|
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| 400 | IStochasticOperator stochasticOp = op as IStochasticOperator;
|
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| 401 | if (stochasticOp != null) {
|
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| 402 | stochasticOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
|
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| 403 | stochasticOp.RandomParameter.Hidden = true;
|
---|
| 404 | }
|
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| 405 | }
|
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| 406 | private void ParameterizeSelectors() {
|
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| 407 | foreach (ISelector selector in SelectorParameter.ValidValues) {
|
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| 408 | selector.CopySelected = new BoolValue(true);
|
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[8377] | 409 | selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * BatchSize.Value);
|
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[8313] | 410 | selector.NumberOfSelectedSubScopesParameter.Hidden = true;
|
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| 411 | ParameterizeStochasticOperator(selector);
|
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| 412 | }
|
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| 413 | if (Problem != null) {
|
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| 414 | foreach (ISingleObjectiveSelector selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
|
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| 415 | selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
|
---|
| 416 | selector.MaximizationParameter.Hidden = true;
|
---|
| 417 | selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
|
---|
| 418 | selector.QualityParameter.Hidden = true;
|
---|
| 419 | }
|
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| 420 | }
|
---|
| 421 | }
|
---|
| 422 | private void ParameterizeAnalyzers() {
|
---|
| 423 | qualityAnalyzer.ResultsParameter.ActualName = "Results";
|
---|
| 424 | qualityAnalyzer.ResultsParameter.Hidden = true;
|
---|
[8377] | 425 | populationSizeAnalyzer.ResultsParameter.ActualName = "Results";
|
---|
| 426 | populationSizeAnalyzer.ResultsParameter.Hidden = true;
|
---|
[8378] | 427 | offspringSuccessAnalyzer.ResultsParameter.ActualName = "Results";
|
---|
| 428 | offspringSuccessAnalyzer.ResultsParameter.Hidden = true;
|
---|
[8385] | 429 | selectionPressureAnalyzer.ResultsParameter.ActualName = "Results";
|
---|
| 430 | selectionPressureAnalyzer.ResultsParameter.Hidden = true;
|
---|
[8313] | 431 | if (Problem != null) {
|
---|
| 432 | qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
|
---|
| 433 | qualityAnalyzer.MaximizationParameter.Hidden = true;
|
---|
| 434 | qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
|
---|
| 435 | qualityAnalyzer.QualityParameter.Depth = 1;
|
---|
| 436 | qualityAnalyzer.QualityParameter.Hidden = true;
|
---|
| 437 | qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
|
---|
| 438 | qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
|
---|
| 439 | }
|
---|
| 440 | }
|
---|
| 441 | private void ParameterizeIterationBasedOperators() {
|
---|
| 442 | if (Problem != null) {
|
---|
| 443 | foreach (IIterationBasedOperator op in Problem.Operators.OfType<IIterationBasedOperator>()) {
|
---|
| 444 | op.IterationsParameter.ActualName = "Generations";
|
---|
| 445 | op.IterationsParameter.Hidden = true;
|
---|
| 446 | op.MaximumIterationsParameter.ActualName = "MaximumGenerations";
|
---|
| 447 | op.MaximumIterationsParameter.Hidden = true;
|
---|
| 448 | }
|
---|
| 449 | }
|
---|
| 450 | }
|
---|
[8407] | 451 | private void ParameterizeSimilarityCalculators() {
|
---|
| 452 | foreach (ISingleObjectiveSolutionSimilarityCalculator calc in SimilarityCalculatorParameter.ValidValues) {
|
---|
| 453 | calc.QualityVariableName = Problem.Evaluator.QualityParameter.ActualName;
|
---|
| 454 | }
|
---|
| 455 | }
|
---|
[8313] | 456 | private void UpdateCrossovers() {
|
---|
| 457 | ICrossover oldCrossover = CrossoverParameter.Value;
|
---|
| 458 | CrossoverParameter.ValidValues.Clear();
|
---|
| 459 | ICrossover defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
|
---|
| 460 |
|
---|
| 461 | foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
|
---|
| 462 | CrossoverParameter.ValidValues.Add(crossover);
|
---|
| 463 |
|
---|
| 464 | if (oldCrossover != null) {
|
---|
| 465 | ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
|
---|
| 466 | if (crossover != null) CrossoverParameter.Value = crossover;
|
---|
| 467 | else oldCrossover = null;
|
---|
| 468 | }
|
---|
| 469 | if (oldCrossover == null && defaultCrossover != null)
|
---|
| 470 | CrossoverParameter.Value = defaultCrossover;
|
---|
| 471 | }
|
---|
| 472 | private void UpdateMutators() {
|
---|
| 473 | IManipulator oldMutator = MutatorParameter.Value;
|
---|
| 474 | MutatorParameter.ValidValues.Clear();
|
---|
| 475 | foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
|
---|
| 476 | MutatorParameter.ValidValues.Add(mutator);
|
---|
| 477 | if (oldMutator != null) {
|
---|
| 478 | IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
|
---|
| 479 | if (mutator != null) MutatorParameter.Value = mutator;
|
---|
| 480 | }
|
---|
| 481 | }
|
---|
| 482 | private void UpdateAnalyzers() {
|
---|
| 483 | Analyzer.Operators.Clear();
|
---|
| 484 | if (Problem != null) {
|
---|
| 485 | foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>()) {
|
---|
| 486 | foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
|
---|
| 487 | param.Depth = 1;
|
---|
| 488 | Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
|
---|
| 489 | }
|
---|
| 490 | }
|
---|
| 491 | Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
|
---|
[8377] | 492 | Analyzer.Operators.Add(populationSizeAnalyzer, populationSizeAnalyzer.EnabledByDefault);
|
---|
[8378] | 493 | Analyzer.Operators.Add(offspringSuccessAnalyzer, offspringSuccessAnalyzer.EnabledByDefault);
|
---|
[8385] | 494 | Analyzer.Operators.Add(selectionPressureAnalyzer, selectionPressureAnalyzer.EnabledByDefault);
|
---|
[8313] | 495 | }
|
---|
[8349] | 496 | private void UpdateSimilarityCalculators() {
|
---|
[8407] | 497 | ISingleObjectiveSolutionSimilarityCalculator oldSimilarityCalculator = SimilarityCalculatorParameter.Value;
|
---|
[8349] | 498 | SimilarityCalculatorParameter.ValidValues.Clear();
|
---|
[8407] | 499 | ISingleObjectiveSolutionSimilarityCalculator defaultSimilarityCalculator = Problem.Operators.OfType<ISingleObjectiveSolutionSimilarityCalculator>().FirstOrDefault();
|
---|
[8349] | 500 |
|
---|
[8407] | 501 | SimilarityCalculatorParameter.ValidValues.Add(new QualitySimilarityCalculator { QualityVariableName = Problem.Evaluator.QualityParameter.ActualName });
|
---|
[8622] | 502 | SimilarityCalculatorParameter.ValidValues.Add(new NoSimilarityCalculator());
|
---|
[8406] | 503 |
|
---|
[8407] | 504 | foreach (ISingleObjectiveSolutionSimilarityCalculator similarityCalculator in Problem.Operators.OfType<ISingleObjectiveSolutionSimilarityCalculator>())
|
---|
[8349] | 505 | SimilarityCalculatorParameter.ValidValues.Add(similarityCalculator);
|
---|
| 506 |
|
---|
| 507 | if (oldSimilarityCalculator != null) {
|
---|
[8407] | 508 | ISingleObjectiveSolutionSimilarityCalculator similarityCalculator = SimilarityCalculatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldSimilarityCalculator.GetType());
|
---|
[8349] | 509 | if (similarityCalculator != null) SimilarityCalculatorParameter.Value = similarityCalculator;
|
---|
| 510 | else oldSimilarityCalculator = null;
|
---|
| 511 | }
|
---|
| 512 | if (oldSimilarityCalculator == null && defaultSimilarityCalculator != null)
|
---|
| 513 | SimilarityCalculatorParameter.Value = defaultSimilarityCalculator;
|
---|
| 514 | }
|
---|
[8313] | 515 | private RAPGAMainLoop FindMainLoop(IOperator start) {
|
---|
| 516 | IOperator mainLoop = start;
|
---|
| 517 | while (mainLoop != null && !(mainLoop is RAPGAMainLoop))
|
---|
| 518 | mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
|
---|
| 519 | if (mainLoop == null) return null;
|
---|
| 520 | else return (RAPGAMainLoop)mainLoop;
|
---|
| 521 | }
|
---|
| 522 | #endregion
|
---|
| 523 | }
|
---|
| 524 | }
|
---|