[11567] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12018] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[11567] | 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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[12531] | 23 | using System.Collections.Generic;
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[11578] | 24 | using System.Linq;
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[11567] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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[11568] | 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Operators;
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[11567] | 29 | using HeuristicLab.Optimization;
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[11578] | 30 | using HeuristicLab.Optimization.Operators;
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[11568] | 31 | using HeuristicLab.Parameters;
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[11567] | 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[11578] | 33 | using HeuristicLab.PluginInfrastructure;
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| 34 | using HeuristicLab.Random;
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| 35 | using HeuristicLab.Selection;
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[11567] | 36 |
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| 37 | namespace HeuristicLab.Algorithms.ALPS {
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| 38 | [Item("ALPS Genetic Algorithm", "A genetic algorithm with an age-layered population structure.")]
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| 39 | [Creatable("Algorithms")]
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| 40 | [StorableClass]
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[12119] | 41 | public sealed class AlpsGeneticAlgorithm : Alps {
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[11567] | 42 | #region Parameter Properties
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[12035] | 43 | private IValueParameter<IntArray> PopulationSizeParameter {
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| 44 | get { return (IValueParameter<IntArray>)Parameters["PopulationSize"]; }
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[11568] | 45 | }
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| 46 | public IConstrainedValueParameter<ISelector> SelectorParameter {
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| 47 | get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
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| 48 | }
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| 49 | public IConstrainedValueParameter<ICrossover> CrossoverParameter {
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| 50 | get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
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| 51 | }
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| 52 | private IValueParameter<PercentValue> MutationProbabilityParameter {
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| 53 | get { return (IValueParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 54 | }
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| 55 | public IConstrainedValueParameter<IManipulator> MutatorParameter {
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| 56 | get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
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| 57 | }
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| 58 | private IValueParameter<IntValue> ElitesParameter {
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| 59 | get { return (IValueParameter<IntValue>)Parameters["Elites"]; }
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| 60 | }
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| 61 | private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
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| 62 | get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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| 63 | }
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[12186] | 64 | private IValueParameter<BoolValue> PlusSelectionParameter {
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| 65 | get { return (IValueParameter<BoolValue>)Parameters["PlusSelection"]; }
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| 66 | }
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[11567] | 67 | #endregion
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| 68 |
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| 69 | #region Properties
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[12035] | 70 | public IntArray PopulationSize {
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[11568] | 71 | get { return PopulationSizeParameter.Value; }
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| 72 | set { PopulationSizeParameter.Value = value; }
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| 73 | }
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| 74 | public ISelector Selector {
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| 75 | get { return SelectorParameter.Value; }
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| 76 | set { SelectorParameter.Value = value; }
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| 77 | }
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| 78 | public ICrossover Crossover {
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| 79 | get { return CrossoverParameter.Value; }
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| 80 | set { CrossoverParameter.Value = value; }
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| 81 | }
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| 82 | public PercentValue MutationProbability {
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| 83 | get { return MutationProbabilityParameter.Value; }
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| 84 | set { MutationProbabilityParameter.Value = value; }
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| 85 | }
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| 86 | public IManipulator Mutator {
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| 87 | get { return MutatorParameter.Value; }
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| 88 | set { MutatorParameter.Value = value; }
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| 89 | }
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| 90 | public IntValue Elites {
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| 91 | get { return ElitesParameter.Value; }
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| 92 | set { ElitesParameter.Value = value; }
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| 93 | }
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| 94 | public bool ReevaluteElites {
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| 95 | get { return ReevaluateElitesParameter.Value.Value; }
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| 96 | set { ReevaluateElitesParameter.Value.Value = value; }
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| 97 | }
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[12186] | 98 | public bool PlusSelection {
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| 99 | get { return PlusSelectionParameter.Value.Value; }
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| 100 | set { PlusSelectionParameter.Value.Value = value; }
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| 101 | }
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[11578] | 102 |
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[11580] | 103 | private AlpsGeneticAlgorithmMainLoop MainLoop {
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| 104 | get { return OperatorGraph.Iterate().OfType<AlpsGeneticAlgorithmMainLoop>().First(); }
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| 105 | }
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[11676] | 106 | #endregion
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| 107 |
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[12531] | 108 | [Storable]
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| 109 | private ComparisonTerminator<IntValue> generationsTerminator;
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| 110 |
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[11567] | 111 | [StorableConstructor]
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| 112 | private AlpsGeneticAlgorithm(bool deserializing)
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| 113 | : base(deserializing) { }
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| 114 | private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
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| 115 | : base(original, cloner) {
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[12531] | 116 | generationsTerminator = cloner.Clone(original.generationsTerminator);
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[11578] | 117 | Initialize();
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[11567] | 118 | }
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| 119 | public override IDeepCloneable Clone(Cloner cloner) {
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| 120 | return new AlpsGeneticAlgorithm(this, cloner);
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| 121 | }
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| 122 | public AlpsGeneticAlgorithm()
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| 123 | : base() {
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[12048] | 124 | Parameters.Add(new ValueParameter<IntArray>("PopulationSize", "The size of the population of solutions each layer.", new IntArray(new[] { 100 })));
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[11568] | 125 | Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
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| 126 | Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
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| 127 | 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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| 128 | Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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| 129 | Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
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| 130 | 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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[12186] | 131 | Parameters.Add(new ValueParameter<BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation.", new BoolValue(false)) { Hidden = true });
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[11578] | 132 |
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| 133 | var globalRandomCreator = new RandomCreator();
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| 134 | var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
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[12035] | 135 | var layer0Processor = new LayerUniformSubScopesProcessor();
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[11578] | 136 | var localRandomCreator = new LocalRandomCreator();
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[11585] | 137 | var layerVariableCreator = new VariableCreator();
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[11578] | 138 | var layerSolutionsCreator = new SolutionsCreator();
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| 139 | var initializeAgeProcessor = new UniformSubScopesProcessor();
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| 140 | var initializeAge = new VariableCreator() { Name = "Initialize Age" };
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[11676] | 141 | var initializeLayerPopulationSize = new SubScopesCounter() { Name = "Init LayerPopulationCounter" };
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| 142 | var initializeLocalEvaluatedSolutions = new Assigner() { Name = "Initialize LayerEvaluatedSolutions" };
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[11578] | 143 | var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
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| 144 | var resultsCollector = new ResultsCollector();
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[11580] | 145 | var mainLoop = new AlpsGeneticAlgorithmMainLoop();
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| 146 |
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[11578] | 147 | OperatorGraph.InitialOperator = globalRandomCreator;
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| 148 |
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| 149 | globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
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| 150 | globalRandomCreator.SeedParameter.Value = null;
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| 151 | globalRandomCreator.SetSeedRandomlyParameter.Value = null;
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| 152 | globalRandomCreator.Successor = layer0Creator;
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| 153 |
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| 154 | layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
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| 155 | layer0Creator.Successor = layer0Processor;
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| 156 |
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[12035] | 157 | layer0Processor.Operator = localRandomCreator;
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[11578] | 158 | layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
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| 159 |
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[11585] | 160 | localRandomCreator.Successor = layerVariableCreator;
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[11578] | 161 |
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[11585] | 162 | layerVariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Layer", new IntValue(0)));
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| 163 | layerVariableCreator.Successor = layerSolutionsCreator;
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| 164 |
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[11578] | 165 | layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
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| 166 | layerSolutionsCreator.Successor = initializeAgeProcessor;
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| 167 |
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| 168 | initializeAgeProcessor.Operator = initializeAge;
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[11676] | 169 | initializeAgeProcessor.Successor = initializeLayerPopulationSize;
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[11578] | 170 |
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[11676] | 171 | initializeLayerPopulationSize.ValueParameter.ActualName = "LayerPopulationSize";
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| 172 | initializeLayerPopulationSize.Successor = initializeLocalEvaluatedSolutions;
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| 173 |
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[11578] | 174 | initializeAge.CollectedValues.Add(new ValueParameter<IntValue>("Age", new IntValue(0)));
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| 175 | initializeAge.Successor = null;
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| 176 |
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[11676] | 177 | initializeLocalEvaluatedSolutions.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
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| 178 | initializeLocalEvaluatedSolutions.RightSideParameter.ActualName = "LayerPopulationSize";
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[11578] | 179 | initializeLocalEvaluatedSolutions.Successor = null;
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| 180 |
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| 181 | initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
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| 182 | initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
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[11590] | 183 | initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
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[11578] | 184 | initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
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| 185 | initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
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| 186 |
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[11609] | 187 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
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[11578] | 188 | resultsCollector.Successor = mainLoop;
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| 189 |
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| 190 | foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
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| 191 | SelectorParameter.ValidValues.Add(selector);
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[12119] | 192 | var tournamentSelector = SelectorParameter.ValidValues.OfType<TournamentSelector>().FirstOrDefault();
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| 193 | if (tournamentSelector != null) {
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[12260] | 194 | tournamentSelector.GroupSizeParameter.Value = new IntValue(4);
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[12119] | 195 | SelectorParameter.Value = tournamentSelector;
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| 196 | }
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[11578] | 197 |
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| 198 | ParameterizeSelectors();
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| 199 | Initialize();
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[11567] | 200 | }
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[11578] | 201 |
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| 202 | #region Events
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| 203 | protected override void OnProblemChanged() {
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[12119] | 204 | base.OnProblemChanged();
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[11578] | 205 | ParameterizeSolutionsCreator();
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| 206 | ParameterizeMainLoop();
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| 207 | ParameterizeSelectors();
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[12120] | 208 | ParameterizeIterationBasedOperators();
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[11578] | 209 | UpdateCrossovers();
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| 210 | UpdateMutators();
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| 211 | }
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| 212 | protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
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[12119] | 213 | base.Problem_SolutionCreatorChanged(sender, e);
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[11578] | 214 | ParameterizeSolutionsCreator();
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| 215 | }
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| 216 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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[12119] | 217 | base.Problem_EvaluatorChanged(sender, e);
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[11578] | 218 | ParameterizeSolutionsCreator();
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| 219 | ParameterizeMainLoop();
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| 220 | ParameterizeSelectors();
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| 221 | }
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| 222 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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[12119] | 223 | base.Problem_OperatorsChanged(sender, e);
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[12120] | 224 | ParameterizeIterationBasedOperators();
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[11578] | 225 | UpdateCrossovers();
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| 226 | UpdateMutators();
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| 227 | }
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[12119] | 228 | protected override void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
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| 229 | base.Evaluator_QualityParameter_ActualNameChanged(sender, e);
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[11578] | 230 | ParameterizeMainLoop();
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| 231 | ParameterizeSelectors();
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| 232 | }
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| 233 | #endregion
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| 234 |
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| 235 | #region Parameterization
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| 236 | private void Initialize() {
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| 237 | }
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| 238 | private void ParameterizeSolutionsCreator() {
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[11590] | 239 | MainLoop.LayerUpdator.SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 240 | MainLoop.LayerUpdator.SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
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[11578] | 241 | }
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| 242 | private void ParameterizeMainLoop() {
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[12045] | 243 | MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 244 | MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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[11583] | 245 | MainLoop.MainOperator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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| 246 | MainLoop.MainOperator.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 247 | MainLoop.MainOperator.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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[11609] | 248 | MainLoop.LayerUpdator.SolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
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[11578] | 249 | }
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| 250 | private void ParameterizeSelectors() {
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| 251 | foreach (var selector in SelectorParameter.ValidValues) {
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| 252 | selector.CopySelected = new BoolValue(true);
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[12035] | 253 | // Explicit setting of NumberOfSelectedSubScopesParameter is not required anymore because the NumberOfSelectedSubScopesCalculator calculates it itself
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| 254 | //selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSize - Elites.Value));
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[11578] | 255 | selector.NumberOfSelectedSubScopesParameter.Hidden = true;
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| 256 | ParameterizeStochasticOperatorForLayer(selector);
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| 257 | }
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| 258 | if (Problem != null) {
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| 259 | foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
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| 260 | selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 261 | selector.MaximizationParameter.Hidden = true;
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| 262 | selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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| 263 | selector.QualityParameter.Hidden = true;
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| 264 | }
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| 265 | }
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| 266 | }
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[12120] | 267 | private void ParameterizeIterationBasedOperators() {
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| 268 | if (Problem != null) {
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| 269 | foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
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| 270 | @operator.IterationsParameter.ActualName = "Generations";
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| 271 | @operator.IterationsParameter.Hidden = true;
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[12531] | 272 | @operator.MaximumIterationsParameter.ActualName = generationsTerminator.ThresholdParameter.Name;
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[12120] | 273 | @operator.MaximumIterationsParameter.Hidden = true;
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| 274 | }
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| 275 | }
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| 276 | }
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[12271] | 277 |
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| 278 | protected override ReductionOperations GetAgeInheritanceReduction(AgeInheritance ageInheritance) {
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| 279 | switch (ageInheritance) {
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| 280 | case ALPS.AgeInheritance.Older: return ReductionOperations.Max;
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| 281 | case ALPS.AgeInheritance.Agerage: return ReductionOperations.Avg;
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| 282 | case ALPS.AgeInheritance.Younger: return ReductionOperations.Min;
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| 283 | default: throw new NotSupportedException("AgeInheritance " + ageInheritance + " is not supported.");
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| 284 | }
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| 285 | }
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[11578] | 286 | #endregion
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| 287 |
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| 288 | #region Updates
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[12531] | 289 | protected override void UpdateTerminators() {
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| 290 | var newTerminators = new Dictionary<ITerminator, bool> {
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| 291 | {generationsTerminator, !Terminators.Operators.Contains(generationsTerminator) || Terminators.Operators.ItemChecked(generationsTerminator)},
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| 292 | };
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| 293 |
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| 294 | base.UpdateTerminators();
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| 295 |
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| 296 | foreach (var newTerminator in newTerminators)
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| 297 | Terminators.Operators.Insert(0, newTerminator.Key, newTerminator.Value);
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| 298 | }
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| 299 | protected override void CreateTerminators() {
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| 300 | generationsTerminator = new ComparisonTerminator<IntValue>("Generations", ComparisonType.Less, new IntValue(1000)) { Name = "Generations" };
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| 301 | base.CreateTerminators();
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| 302 | }
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[11578] | 303 | private void UpdateCrossovers() {
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| 304 | var oldCrossover = CrossoverParameter.Value;
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| 305 | var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
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| 306 | CrossoverParameter.ValidValues.Clear();
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| 307 | foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
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| 308 | ParameterizeStochasticOperatorForLayer(crossover);
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| 309 | CrossoverParameter.ValidValues.Add(crossover);
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| 310 | }
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| 311 | if (oldCrossover != null) {
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| 312 | var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
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[11678] | 313 | if (crossover != null)
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| 314 | CrossoverParameter.Value = crossover;
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| 315 | else
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| 316 | oldCrossover = null;
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[11578] | 317 | }
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| 318 | if (oldCrossover == null && defaultCrossover != null)
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| 319 | CrossoverParameter.Value = defaultCrossover;
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| 320 | }
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| 321 | private void UpdateMutators() {
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| 322 | var oldMutator = MutatorParameter.Value;
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| 323 | MutatorParameter.ValidValues.Clear();
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| 324 | foreach (var mutator in Problem.Operators.OfType<IManipulator>().OrderBy(m => m.Name)) {
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| 325 | ParameterizeStochasticOperatorForLayer(mutator);
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| 326 | MutatorParameter.ValidValues.Add(mutator);
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| 327 | }
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| 328 | if (oldMutator != null) {
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| 329 | var mutator = MutatorParameter.ValidValues.FirstOrDefault(m => m.GetType() == oldMutator.GetType());
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[11678] | 330 | if (mutator != null)
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| 331 | MutatorParameter.Value = mutator;
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[11578] | 332 | }
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| 333 | }
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| 334 | #endregion
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[11567] | 335 | }
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| 336 | } |
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