| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using 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.Random;
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| 34 |
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| 35 | namespace HeuristicLab.Algorithms.EvolutionStrategy {
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| 36 | [Item("Evolution Strategy (ES)", "An evolution strategy.")]
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| 37 | [Creatable(CreatableAttribute.Categories.PopulationBasedAlgorithms, Priority = 200)]
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| 38 | [StorableType("10B6FC65-8B3F-44B8-AD9B-B26505D84167")]
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| 39 | public sealed class EvolutionStrategy : HeuristicOptimizationEngineAlgorithm, IStorableContent {
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| 40 | public string Filename { get; set; }
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| 41 |
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| 42 | #region Problem Properties
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| 43 | public override Type ProblemType {
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| 44 | get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
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| 45 | }
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| 46 | public new ISingleObjectiveHeuristicOptimizationProblem Problem {
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| 47 | get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
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| 48 | set { base.Problem = value; }
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| 49 | }
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| 50 | #endregion
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| 51 |
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| 52 | #region Parameter Properties
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| 53 | private ValueParameter<IntValue> SeedParameter {
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| 54 | get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
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| 55 | }
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| 56 | private ValueParameter<BoolValue> SetSeedRandomlyParameter {
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| 57 | get { return (ValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
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| 58 | }
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| 59 | private ValueParameter<IntValue> PopulationSizeParameter {
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| 60 | get { return (ValueParameter<IntValue>)Parameters["PopulationSize"]; }
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| 61 | }
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| 62 | private ValueParameter<IntValue> ParentsPerChildParameter {
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| 63 | get { return (ValueParameter<IntValue>)Parameters["ParentsPerChild"]; }
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| 64 | }
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| 65 | private ValueParameter<IntValue> ChildrenParameter {
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| 66 | get { return (ValueParameter<IntValue>)Parameters["Children"]; }
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| 67 | }
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| 68 | private ValueParameter<IntValue> MaximumGenerationsParameter {
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| 69 | get { return (ValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 70 | }
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| 71 | private ValueParameter<BoolValue> PlusSelectionParameter {
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| 72 | get { return (ValueParameter<BoolValue>)Parameters["PlusSelection"]; }
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| 73 | }
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| 74 | private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
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| 75 | get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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| 76 | }
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| 77 | public IConstrainedValueParameter<IManipulator> MutatorParameter {
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| 78 | get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
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| 79 | }
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| 80 | public IConstrainedValueParameter<ICrossover> RecombinatorParameter {
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| 81 | get { return (IConstrainedValueParameter<ICrossover>)Parameters["Recombinator"]; }
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| 82 | }
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| 83 | private ValueParameter<MultiAnalyzer> AnalyzerParameter {
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| 84 | get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
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| 85 | }
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| 86 | public IConstrainedValueParameter<IStrategyParameterCreator> StrategyParameterCreatorParameter {
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| 87 | get { return (IConstrainedValueParameter<IStrategyParameterCreator>)Parameters["StrategyParameterCreator"]; }
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| 88 | }
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| 89 | public IConstrainedValueParameter<IStrategyParameterCrossover> StrategyParameterCrossoverParameter {
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| 90 | get { return (IConstrainedValueParameter<IStrategyParameterCrossover>)Parameters["StrategyParameterCrossover"]; }
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| 91 | }
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| 92 | public IConstrainedValueParameter<IStrategyParameterManipulator> StrategyParameterManipulatorParameter {
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| 93 | get { return (IConstrainedValueParameter<IStrategyParameterManipulator>)Parameters["StrategyParameterManipulator"]; }
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| 94 | }
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| 95 | #endregion
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| 96 |
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| 97 | #region Properties
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| 98 | public IntValue Seed {
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| 99 | get { return SeedParameter.Value; }
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| 100 | set { SeedParameter.Value = value; }
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| 101 | }
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| 102 | public BoolValue SetSeedRandomly {
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| 103 | get { return SetSeedRandomlyParameter.Value; }
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| 104 | set { SetSeedRandomlyParameter.Value = value; }
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| 105 | }
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| 106 | public IntValue PopulationSize {
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| 107 | get { return PopulationSizeParameter.Value; }
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| 108 | set { PopulationSizeParameter.Value = value; }
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| 109 | }
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| 110 | public IntValue ParentsPerChild {
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| 111 | get { return ParentsPerChildParameter.Value; }
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| 112 | set { ParentsPerChildParameter.Value = value; }
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| 113 | }
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| 114 | public IntValue Children {
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| 115 | get { return ChildrenParameter.Value; }
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| 116 | set { ChildrenParameter.Value = value; }
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| 117 | }
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| 118 | public IntValue MaximumGenerations {
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| 119 | get { return MaximumGenerationsParameter.Value; }
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| 120 | set { MaximumGenerationsParameter.Value = value; }
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| 121 | }
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| 122 | public BoolValue PlusSelection {
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| 123 | get { return PlusSelectionParameter.Value; }
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| 124 | set { PlusSelectionParameter.Value = value; }
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| 125 | }
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| 126 | public bool ReevaluteElites {
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| 127 | get { return ReevaluateElitesParameter.Value.Value; }
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| 128 | set { ReevaluateElitesParameter.Value.Value = value; }
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| 129 | }
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| 130 | public IManipulator Mutator {
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| 131 | get { return MutatorParameter.Value; }
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| 132 | set { MutatorParameter.Value = value; }
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| 133 | }
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| 134 | public ICrossover Recombinator {
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| 135 | get { return RecombinatorParameter.Value; }
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| 136 | set { RecombinatorParameter.Value = value; }
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| 137 | }
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| 138 | public MultiAnalyzer Analyzer {
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| 139 | get { return AnalyzerParameter.Value; }
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| 140 | set { AnalyzerParameter.Value = value; }
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| 141 | }
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| 142 | public IStrategyParameterCreator StrategyParameterCreator {
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| 143 | get { return StrategyParameterCreatorParameter.Value; }
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| 144 | set { StrategyParameterCreatorParameter.Value = value; }
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| 145 | }
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| 146 | public IStrategyParameterCrossover StrategyParameterCrossover {
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| 147 | get { return StrategyParameterCrossoverParameter.Value; }
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| 148 | set { StrategyParameterCrossoverParameter.Value = value; }
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| 149 | }
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| 150 | public IStrategyParameterManipulator StrategyParameterManipulator {
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| 151 | get { return StrategyParameterManipulatorParameter.Value; }
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| 152 | set { StrategyParameterManipulatorParameter.Value = value; }
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| 153 | }
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| 154 |
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| 155 | private RandomCreator RandomCreator {
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| 156 | get { return (RandomCreator)OperatorGraph.InitialOperator; }
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| 157 | }
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| 158 | private SolutionsCreator SolutionsCreator {
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| 159 | get { return (SolutionsCreator)RandomCreator.Successor; }
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| 160 | }
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| 161 | private EvolutionStrategyMainLoop MainLoop {
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| 162 | get { return FindMainLoop(SolutionsCreator.Successor); }
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| 163 | }
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| 164 | [Storable]
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| 165 | private BestAverageWorstQualityAnalyzer qualityAnalyzer;
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| 166 | #endregion
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| 167 |
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| 168 | public EvolutionStrategy()
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| 169 | : base() {
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| 170 | 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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| 171 | 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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| 172 | Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "µ (mu) - the size of the population.", new IntValue(20)));
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| 173 | Parameters.Add(new ValueParameter<IntValue>("ParentsPerChild", "Ï (rho) - how many parents should be recombined.", new IntValue(1)));
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| 174 | Parameters.Add(new ValueParameter<IntValue>("Children", "λ (lambda) - the size of the offspring population.", new IntValue(100)));
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| 175 | Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed.", new IntValue(1000)));
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| 176 | Parameters.Add(new ValueParameter<BoolValue>("PlusSelection", "True for plus selection (elitist population), false for comma selection (non-elitist population).", new BoolValue(true)));
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| 177 | 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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| 178 | Parameters.Add(new OptionalConstrainedValueParameter<ICrossover>("Recombinator", "The operator used to cross solutions."));
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| 179 | Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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| 180 | Parameters.Add(new OptionalConstrainedValueParameter<IStrategyParameterCreator>("StrategyParameterCreator", "The operator that creates the strategy parameters."));
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| 181 | Parameters.Add(new OptionalConstrainedValueParameter<IStrategyParameterCrossover>("StrategyParameterCrossover", "The operator that recombines the strategy parameters."));
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| 182 | Parameters.Add(new OptionalConstrainedValueParameter<IStrategyParameterManipulator>("StrategyParameterManipulator", "The operator that manipulates the strategy parameters."));
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| 183 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
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| 184 |
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| 185 | RandomCreator randomCreator = new RandomCreator();
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| 186 | SolutionsCreator solutionsCreator = new SolutionsCreator();
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| 187 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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| 188 | UniformSubScopesProcessor strategyVectorProcessor = new UniformSubScopesProcessor();
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| 189 | Placeholder strategyVectorCreator = new Placeholder();
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| 190 | ResultsCollector resultsCollector = new ResultsCollector();
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| 191 | EvolutionStrategyMainLoop mainLoop = new EvolutionStrategyMainLoop();
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| 192 | OperatorGraph.InitialOperator = randomCreator;
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| 193 |
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| 194 | randomCreator.RandomParameter.ActualName = "Random";
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| 195 | randomCreator.SeedParameter.ActualName = SeedParameter.Name;
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| 196 | randomCreator.SeedParameter.Value = null;
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| 197 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
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| 198 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 199 | randomCreator.Successor = solutionsCreator;
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| 200 |
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| 201 | solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
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| 202 | solutionsCreator.Successor = subScopesCounter;
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| 203 |
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| 204 | subScopesCounter.Name = "Initialize EvaluatedSolutions";
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| 205 | subScopesCounter.ValueParameter.ActualName = "EvaluatedSolutions";
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| 206 | subScopesCounter.Successor = strategyVectorProcessor;
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| 207 |
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| 208 | strategyVectorProcessor.Operator = strategyVectorCreator;
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| 209 | strategyVectorProcessor.Successor = resultsCollector;
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| 210 |
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| 211 | strategyVectorCreator.OperatorParameter.ActualName = "StrategyParameterCreator";
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| 212 |
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| 213 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
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| 214 | resultsCollector.ResultsParameter.ActualName = "Results";
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| 215 | resultsCollector.Successor = mainLoop;
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| 216 |
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| 217 | mainLoop.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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| 218 | mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
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| 219 | mainLoop.ParentsPerChildParameter.ActualName = ParentsPerChildParameter.Name;
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| 220 | mainLoop.ChildrenParameter.ActualName = ChildrenParameter.Name;
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| 221 | mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
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| 222 | mainLoop.PlusSelectionParameter.ActualName = PlusSelectionParameter.Name;
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| 223 | mainLoop.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
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| 224 | mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
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| 225 | mainLoop.RecombinatorParameter.ActualName = RecombinatorParameter.Name;
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| 226 | mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
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| 227 | mainLoop.ResultsParameter.ActualName = "Results";
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| 228 | mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
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| 229 |
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| 230 | qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
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| 231 | ParameterizeAnalyzers();
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| 232 | UpdateAnalyzers();
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| 233 |
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| 234 | Initialize();
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| 235 | }
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| 236 | [StorableConstructor]
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| 237 | private EvolutionStrategy(bool deserializing) : base(deserializing) { }
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| 238 | [StorableHook(HookType.AfterDeserialization)]
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| 239 | private void AfterDeserialization() {
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| 240 | // BackwardsCompatibility3.3
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| 241 | #region Backwards compatible code, remove with 3.4
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| 242 | if (!Parameters.ContainsKey("ReevaluateElites")) {
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| 243 | 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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| 244 | }
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| 245 | #endregion
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| 246 |
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| 247 | Initialize();
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| 248 | }
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| 249 |
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| 250 | private EvolutionStrategy(EvolutionStrategy original, Cloner cloner)
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| 251 | : base(original, cloner) {
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| 252 | qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
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| 253 | Initialize();
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| 254 | }
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| 255 | public override IDeepCloneable Clone(Cloner cloner) {
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| 256 | return new EvolutionStrategy(this, cloner);
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| 257 | }
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| 258 |
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| 259 | public override void Prepare() {
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| 260 | if (Problem != null) base.Prepare();
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| 261 | }
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| 262 |
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| 263 | #region Events
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| 264 | protected override void OnProblemChanged() {
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| 265 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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| 266 | ParameterizeStochasticOperator(Problem.Evaluator);
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| 267 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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| 268 | ParameterizeSolutionsCreator();
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| 269 | ParameterizeMainLoop();
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| 270 | ParameterizeAnalyzers();
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| 271 | ParameterizeIterationBasedOperators();
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| 272 | UpdateRecombinators();
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| 273 | UpdateMutators();
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| 274 | UpdateAnalyzers();
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| 275 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 276 | base.OnProblemChanged();
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| 277 | }
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| 278 | protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
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| 279 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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| 280 | ParameterizeSolutionsCreator();
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| 281 | base.Problem_SolutionCreatorChanged(sender, e);
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| 282 | }
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| 283 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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| 284 | ParameterizeStochasticOperator(Problem.Evaluator);
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| 285 | ParameterizeSolutionsCreator();
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| 286 | ParameterizeMainLoop();
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| 287 | ParameterizeAnalyzers();
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| 288 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 289 | base.Problem_EvaluatorChanged(sender, e);
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| 290 | }
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| 291 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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| 292 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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| 293 | ParameterizeIterationBasedOperators();
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| 294 | UpdateRecombinators();
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| 295 | UpdateMutators();
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| 296 | UpdateAnalyzers();
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| 297 | base.Problem_OperatorsChanged(sender, e);
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| 298 | }
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| 299 | private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
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| 300 | ParameterizeMainLoop();
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| 301 | ParameterizeAnalyzers();
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| 302 | }
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| 303 | private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
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| 304 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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| 305 | PopulationSize_ValueChanged(null, EventArgs.Empty);
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| 306 | }
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| 307 | private void PopulationSize_ValueChanged(object sender, EventArgs e) {
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| 308 | if (PopulationSize.Value <= 0) PopulationSize.Value = 1;
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| 309 | if (!PlusSelection.Value && Children.Value < PopulationSize.Value)
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| 310 | Children.Value = PopulationSize.Value;
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| 311 | if (PopulationSize.Value < ParentsPerChild.Value)
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| 312 | ParentsPerChild.Value = PopulationSize.Value;
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| 313 | }
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| 314 | private void ParentsPerChildParameter_ValueChanged(object sender, EventArgs e) {
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| 315 | ParentsPerChild.ValueChanged += new EventHandler(ParentsPerChild_ValueChanged);
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| 316 | ParentsPerChild_ValueChanged(null, EventArgs.Empty);
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| 317 | }
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| 318 | private void ParentsPerChild_ValueChanged(object sender, EventArgs e) {
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| 319 | if (ParentsPerChild.Value < 1 || ParentsPerChild.Value > 1 && RecombinatorParameter.ValidValues.Count == 0)
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| 320 | ParentsPerChild.Value = 1;
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| 321 | if (ParentsPerChild.Value > 1 && Recombinator == null) Recombinator = RecombinatorParameter.ValidValues.First();
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| 322 | if (ParentsPerChild.Value > 1 && ParentsPerChild.Value > PopulationSize.Value)
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| 323 | PopulationSize.Value = ParentsPerChild.Value;
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| 324 | }
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| 325 | private void ChildrenParameter_ValueChanged(object sender, EventArgs e) {
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| 326 | Children.ValueChanged += new EventHandler(Children_ValueChanged);
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| 327 | Children_ValueChanged(null, EventArgs.Empty);
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| 328 | }
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| 329 | private void Children_ValueChanged(object sender, EventArgs e) {
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| 330 | if (Children.Value <= 0) Children.Value = 1;
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| 331 | if (!PlusSelection.Value && Children.Value < PopulationSize.Value)
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| 332 | PopulationSize.Value = Children.Value;
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| 333 | }
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| 334 | private void PlusSelectionParameter_ValueChanged(object sender, EventArgs e) {
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| 335 | PlusSelection.ValueChanged += new EventHandler(PlusSelection_ValueChanged);
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| 336 | PlusSelection_ValueChanged(null, EventArgs.Empty);
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| 337 | }
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| 338 | private void PlusSelection_ValueChanged(object sender, EventArgs e) {
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| 339 | if (!PlusSelection.Value && Children.Value < PopulationSize.Value)
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| 340 | Children.Value = PopulationSize.Value;
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| 341 | }
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| 342 | private void RecombinatorParameter_ValueChanged(object sender, EventArgs e) {
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| 343 | if (Recombinator == null && ParentsPerChild.Value > 1) ParentsPerChild.Value = 1;
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| 344 | else if (Recombinator != null && ParentsPerChild.Value == 1) ParentsPerChild.Value = 2;
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| 345 | if (Recombinator != null && Mutator is ISelfAdaptiveManipulator && StrategyParameterCrossover == null) {
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| 346 | if (StrategyParameterCrossoverParameter.ValidValues.Count > 0)
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| 347 | StrategyParameterCrossover = StrategyParameterCrossoverParameter.ValidValues.First();
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| 348 | }
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| 349 | }
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| 350 | private void MutatorParameter_ValueChanged(object sender, EventArgs e) {
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| 351 | if (Mutator is ISelfAdaptiveManipulator) {
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| 352 | UpdateStrategyParameterOperators();
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| 353 | } else {
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| 354 | StrategyParameterCreatorParameter.ValidValues.Clear();
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| 355 | StrategyParameterCrossoverParameter.ValidValues.Clear();
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| 356 | StrategyParameterManipulatorParameter.ValidValues.Clear();
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| 357 | UpdateRecombinators();
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| 358 | }
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| 359 | }
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| 360 | private void StrategyParameterCreatorParameter_ValueChanged(object sender, EventArgs e) {
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| 361 | if (Mutator is ISelfAdaptiveManipulator && StrategyParameterCreator == null && StrategyParameterCreatorParameter.ValidValues.Count > 0)
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| 362 | StrategyParameterCreator = StrategyParameterCreatorParameter.ValidValues.First();
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| 363 | }
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| 364 | private void StrategyParameterCrossoverParameter_ValueChanged(object sender, EventArgs e) {
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| 365 | if (Mutator is ISelfAdaptiveManipulator && Recombinator != null && StrategyParameterCrossover == null && StrategyParameterCrossoverParameter.ValidValues.Count > 0)
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| 366 | StrategyParameterCrossover = StrategyParameterCrossoverParameter.ValidValues.First();
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| 367 | }
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| 368 | #endregion
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| 369 |
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| 370 | #region Helpers
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| 371 | private void Initialize() {
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| 372 | PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
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| 373 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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| 374 | ParentsPerChildParameter.ValueChanged += new EventHandler(ParentsPerChildParameter_ValueChanged);
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| 375 | ParentsPerChild.ValueChanged += new EventHandler(ParentsPerChild_ValueChanged);
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| 376 | ChildrenParameter.ValueChanged += new EventHandler(ChildrenParameter_ValueChanged);
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| 377 | Children.ValueChanged += new EventHandler(Children_ValueChanged);
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| 378 | PlusSelectionParameter.ValueChanged += new EventHandler(PlusSelectionParameter_ValueChanged);
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| 379 | PlusSelection.ValueChanged += new EventHandler(PlusSelection_ValueChanged);
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| 380 | RecombinatorParameter.ValueChanged += new EventHandler(RecombinatorParameter_ValueChanged);
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| 381 | MutatorParameter.ValueChanged += new EventHandler(MutatorParameter_ValueChanged);
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| 382 | StrategyParameterCrossoverParameter.ValueChanged += new EventHandler(StrategyParameterCrossoverParameter_ValueChanged);
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| 383 | StrategyParameterCreatorParameter.ValueChanged += new EventHandler(StrategyParameterCreatorParameter_ValueChanged);
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| 384 | if (Problem != null)
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| 385 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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| 386 | }
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| 387 | private void ParameterizeSolutionsCreator() {
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| 388 | SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 389 | SolutionsCreator.EvaluatorParameter.Hidden = true;
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| 390 | SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
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| 391 | SolutionsCreator.SolutionCreatorParameter.Hidden = true;
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| 392 | }
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| 393 | private void ParameterizeMainLoop() {
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| 394 | MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
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| 395 | MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 396 | MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 397 | MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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| 398 | }
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| 399 | private void ParameterizeStochasticOperator(IOperator op) {
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| 400 | if (op is IStochasticOperator) {
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| 401 | IStochasticOperator stOp = (IStochasticOperator)op;
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| 402 | stOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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| 403 | stOp.RandomParameter.Hidden = true;
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| 404 | }
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| 405 | }
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| 406 | private void ParameterizeAnalyzers() {
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| 407 | qualityAnalyzer.ResultsParameter.ActualName = "Results";
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| 408 | qualityAnalyzer.ResultsParameter.Hidden = true;
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| 409 | if (Problem != null) {
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| 410 | qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 411 | qualityAnalyzer.MaximizationParameter.Hidden = true;
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| 412 | qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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| 413 | qualityAnalyzer.QualityParameter.Depth = 1;
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| 414 | qualityAnalyzer.QualityParameter.Hidden = true;
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| 415 | qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
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| 416 | qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
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| 417 | } else {
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| 418 | qualityAnalyzer.MaximizationParameter.Hidden = false;
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| 419 | qualityAnalyzer.QualityParameter.Hidden = false;
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| 420 | qualityAnalyzer.BestKnownQualityParameter.Hidden = false;
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| 421 | }
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| 422 | }
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| 423 | private void ParameterizeIterationBasedOperators() {
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| 424 | if (Problem != null) {
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| 425 | foreach (IIterationBasedOperator op in Problem.Operators.OfType<IIterationBasedOperator>()) {
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| 426 | op.IterationsParameter.ActualName = "Generations";
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| 427 | op.IterationsParameter.Hidden = true;
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| 428 | op.MaximumIterationsParameter.ActualName = "MaximumGenerations";
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| 429 | op.MaximumIterationsParameter.Hidden = true;
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| 430 | }
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| 431 | }
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| 432 | }
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| 433 | private void UpdateStrategyParameterOperators() {
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| 434 | IStrategyParameterCreator oldStrategyCreator = StrategyParameterCreator;
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| 435 | IStrategyParameterCrossover oldStrategyCrossover = StrategyParameterCrossover;
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| 436 | IStrategyParameterManipulator oldStrategyManipulator = StrategyParameterManipulator;
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| 437 | ClearStrategyParameterOperators();
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| 438 | ISelfAdaptiveManipulator manipulator = (Mutator as ISelfAdaptiveManipulator);
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| 439 | if (manipulator != null) {
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| 440 | var operators = Problem.Operators.OfType<IOperator>().Where(x => manipulator.StrategyParameterType.IsAssignableFrom(x.GetType())).OrderBy(x => x.Name);
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| 441 | foreach (IStrategyParameterCreator strategyCreator in operators.OfType<IStrategyParameterCreator>())
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| 442 | StrategyParameterCreatorParameter.ValidValues.Add(strategyCreator);
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| 443 | foreach (IStrategyParameterCrossover strategyRecombinator in operators.OfType<IStrategyParameterCrossover>())
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| 444 | StrategyParameterCrossoverParameter.ValidValues.Add(strategyRecombinator);
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| 445 | foreach (IStrategyParameterManipulator strategyManipulator in operators.OfType<IStrategyParameterManipulator>())
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| 446 | StrategyParameterManipulatorParameter.ValidValues.Add(strategyManipulator);
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| 447 |
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| 448 | if (StrategyParameterCrossoverParameter.ValidValues.Count == 0)
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| 449 | RecombinatorParameter.ValidValues.Clear(); // if there is no strategy parameter crossover, there can be no crossover when the mutation operator needs strategy parameters
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| 450 |
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| 451 | if (oldStrategyCreator != null) {
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| 452 | IStrategyParameterCreator tmp1 = StrategyParameterCreatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldStrategyCreator.GetType());
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| 453 | if (tmp1 != null) StrategyParameterCreator = tmp1;
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| 454 | } else if (StrategyParameterCreatorParameter.ValidValues.Count > 0) StrategyParameterCreator = StrategyParameterCreatorParameter.ValidValues.First();
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| 455 | if (oldStrategyCrossover != null) {
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| 456 | IStrategyParameterCrossover tmp2 = StrategyParameterCrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldStrategyCrossover.GetType());
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| 457 | if (tmp2 != null) StrategyParameterCrossover = tmp2;
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| 458 | } else if (StrategyParameterCrossoverParameter.ValidValues.Count > 0) StrategyParameterCrossover = StrategyParameterCrossoverParameter.ValidValues.First();
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| 459 | if (oldStrategyManipulator != null) {
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| 460 | IStrategyParameterManipulator tmp3 = StrategyParameterManipulatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldStrategyManipulator.GetType());
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| 461 | if (tmp3 != null) StrategyParameterManipulator = tmp3;
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| 462 | } else if (StrategyParameterManipulatorParameter.ValidValues.Count > 0) StrategyParameterManipulator = StrategyParameterManipulatorParameter.ValidValues.First();
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| 463 | }
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| 464 | }
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| 465 | private void ClearStrategyParameterOperators() {
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| 466 | StrategyParameterCreatorParameter.ValidValues.Clear();
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| 467 | StrategyParameterCrossoverParameter.ValidValues.Clear();
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| 468 | StrategyParameterManipulatorParameter.ValidValues.Clear();
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| 469 | }
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| 470 | private void UpdateRecombinators() {
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| 471 | ICrossover oldRecombinator = Recombinator;
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| 472 | RecombinatorParameter.ValidValues.Clear();
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| 473 | foreach (ICrossover recombinator in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name)) {
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| 474 | RecombinatorParameter.ValidValues.Add(recombinator);
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| 475 | }
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| 476 | if (oldRecombinator != null) {
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| 477 | ICrossover recombinator = RecombinatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldRecombinator.GetType());
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| 478 | if (recombinator != null) RecombinatorParameter.Value = recombinator;
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| 479 | }
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| 480 | }
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| 481 | private void UpdateMutators() {
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| 482 | IManipulator oldMutator = MutatorParameter.Value;
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| 483 | MutatorParameter.ValidValues.Clear();
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| 484 | foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
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| 485 | MutatorParameter.ValidValues.Add(mutator);
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| 486 | if (oldMutator != null) {
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| 487 | IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
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| 488 | if (mutator != null) MutatorParameter.Value = mutator;
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| 489 | } else if (MutatorParameter.ValidValues.Count > 0 && Problem.Operators.OfType<ISelfAdaptiveManipulator>().Count() > 0) {
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| 490 | ISelfAdaptiveManipulator mutator = Problem.Operators.OfType<ISelfAdaptiveManipulator>().First();
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| 491 | if (mutator != null) MutatorParameter.Value = mutator;
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| 492 | }
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| 493 | }
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| 494 | private void UpdateAnalyzers() {
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| 495 | Analyzer.Operators.Clear();
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| 496 | if (Problem != null) {
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| 497 | foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>()) {
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| 498 | foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
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| 499 | param.Depth = 1;
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| 500 | Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
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| 501 | }
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| 502 | }
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| 503 | Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
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| 504 | }
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| 505 | private EvolutionStrategyMainLoop FindMainLoop(IOperator start) {
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| 506 | IOperator mainLoop = start;
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| 507 | while (mainLoop != null && !(mainLoop is EvolutionStrategyMainLoop))
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| 508 | mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
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| 509 | if (mainLoop == null) return null;
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| 510 | else return (EvolutionStrategyMainLoop)mainLoop;
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| 511 | }
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| 512 | #endregion
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| 513 | }
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| 514 | }
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