| 1 | #region License Information
|
|---|
| 2 | /* HeuristicLab
|
|---|
| 3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
|---|
| 4 | *
|
|---|
| 5 | * This file is part of HeuristicLab.
|
|---|
| 6 | *
|
|---|
| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
|
|---|
| 8 | * it under the terms of the GNU General Public License as published by
|
|---|
| 9 | * the Free Software Foundation, either version 3 of the License, or
|
|---|
| 10 | * (at your option) any later version.
|
|---|
| 11 | *
|
|---|
| 12 | * HeuristicLab is distributed in the hope that it will be useful,
|
|---|
| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|---|
| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|---|
| 15 | * GNU General Public License for more details.
|
|---|
| 16 | *
|
|---|
| 17 | * You should have received a copy of the GNU General Public License
|
|---|
| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
|---|
| 19 | */
|
|---|
| 20 | #endregion
|
|---|
| 21 |
|
|---|
| 22 | using HeuristicLab.Common;
|
|---|
| 23 | using HeuristicLab.Core;
|
|---|
| 24 | using HeuristicLab.Data;
|
|---|
| 25 | using HeuristicLab.Operators;
|
|---|
| 26 | using HeuristicLab.Optimization.Operators;
|
|---|
| 27 | using HeuristicLab.Parameters;
|
|---|
| 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
|---|
| 29 | using HeuristicLab.Selection;
|
|---|
| 30 |
|
|---|
| 31 | namespace HeuristicLab.Algorithms.GAssist {
|
|---|
| 32 | /// <summary>
|
|---|
| 33 | /// An operator which represents the main loop of a genetic algorithm.
|
|---|
| 34 | /// </summary>
|
|---|
| 35 | [Item("GAssistMainLoop", "An operator which represents the main loop of GAssist.")]
|
|---|
| 36 | [StorableClass]
|
|---|
| 37 | public sealed class GAssistMainLoop : AlgorithmOperator {
|
|---|
| 38 | #region Parameter properties
|
|---|
| 39 | public ValueLookupParameter<IRandom> RandomParameter {
|
|---|
| 40 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
|
|---|
| 41 | }
|
|---|
| 42 | public ValueLookupParameter<BoolValue> MaximizationParameter {
|
|---|
| 43 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
|
|---|
| 44 | }
|
|---|
| 45 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
|
|---|
| 46 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
|
|---|
| 47 | }
|
|---|
| 48 | public ValueLookupParameter<IOperator> SelectorParameter {
|
|---|
| 49 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
|
|---|
| 50 | }
|
|---|
| 51 | public ValueLookupParameter<PercentValue> CrossoverProbabilityParameter {
|
|---|
| 52 | get { return (ValueLookupParameter<PercentValue>)Parameters["CrossoverProbability"]; }
|
|---|
| 53 | }
|
|---|
| 54 | public ValueLookupParameter<IOperator> CrossoverParameter {
|
|---|
| 55 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
|
|---|
| 56 | }
|
|---|
| 57 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
|
|---|
| 58 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
|
|---|
| 59 | }
|
|---|
| 60 | public ValueLookupParameter<IOperator> MutatorParameter {
|
|---|
| 61 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
|
|---|
| 62 | }
|
|---|
| 63 | public ValueLookupParameter<IOperator> SpecialStagesParameter {
|
|---|
| 64 | get { return (ValueLookupParameter<IOperator>)Parameters["SpecialStages"]; }
|
|---|
| 65 | }
|
|---|
| 66 | public ValueLookupParameter<IOperator> EvaluatorParameter {
|
|---|
| 67 | get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
|
|---|
| 68 | }
|
|---|
| 69 | public ValueLookupParameter<IntValue> ElitesParameter {
|
|---|
| 70 | get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
|
|---|
| 71 | }
|
|---|
| 72 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
|
|---|
| 73 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
|
|---|
| 74 | }
|
|---|
| 75 | public ValueLookupParameter<VariableCollection> ResultsParameter {
|
|---|
| 76 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
|
|---|
| 77 | }
|
|---|
| 78 | public ValueLookupParameter<IOperator> AnalyzerParameter {
|
|---|
| 79 | get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
|
|---|
| 80 | }
|
|---|
| 81 | public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
|
|---|
| 82 | get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
|
|---|
| 83 | }
|
|---|
| 84 | public ValueLookupParameter<IntValue> PopulationSizeParameter {
|
|---|
| 85 | get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
|
|---|
| 86 | }
|
|---|
| 87 | private ScopeParameter CurrentScopeParameter {
|
|---|
| 88 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
|
|---|
| 89 | }
|
|---|
| 90 |
|
|---|
| 91 | public IScope CurrentScope {
|
|---|
| 92 | get { return CurrentScopeParameter.ActualValue; }
|
|---|
| 93 | }
|
|---|
| 94 | #endregion
|
|---|
| 95 |
|
|---|
| 96 | [StorableConstructor]
|
|---|
| 97 | private GAssistMainLoop(bool deserializing) : base(deserializing) { }
|
|---|
| 98 | private GAssistMainLoop(GAssistMainLoop original, Cloner cloner)
|
|---|
| 99 | : base(original, cloner) {
|
|---|
| 100 | }
|
|---|
| 101 | public override IDeepCloneable Clone(Cloner cloner) {
|
|---|
| 102 | return new GAssistMainLoop(this, cloner);
|
|---|
| 103 | }
|
|---|
| 104 | public GAssistMainLoop()
|
|---|
| 105 | : base() {
|
|---|
| 106 | Initialize();
|
|---|
| 107 | }
|
|---|
| 108 |
|
|---|
| 109 | private void Initialize() {
|
|---|
| 110 | #region Create parameters
|
|---|
| 111 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
|
|---|
| 112 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
|
|---|
| 113 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
|
|---|
| 114 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
|
|---|
| 115 | Parameters.Add(new ValueLookupParameter<PercentValue>("CrossoverProbability", "The probability that the crossover operator is applied on a solution."));
|
|---|
| 116 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
|
|---|
| 117 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
|
|---|
| 118 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
|
|---|
| 119 | Parameters.Add(new ValueLookupParameter<IOperator>("SpecialStages", "The operator used for the special stages of GAssist."));
|
|---|
| 120 | Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
|
|---|
| 121 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
|
|---|
| 122 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
|
|---|
| 123 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
|
|---|
| 124 | Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
|
|---|
| 125 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
|
|---|
| 126 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
|
|---|
| 127 | Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the genetic algorithm should be applied."));
|
|---|
| 128 | #endregion
|
|---|
| 129 |
|
|---|
| 130 | #region Create operators
|
|---|
| 131 | VariableCreator variableCreator = new VariableCreator();
|
|---|
| 132 | ResultsCollector resultsCollector1 = new ResultsCollector();
|
|---|
| 133 | Placeholder analyzer1 = new Placeholder();
|
|---|
| 134 | Placeholder selector = new Placeholder();
|
|---|
| 135 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
|
|---|
| 136 | ChildrenCreator childrenCreator = new ChildrenCreator();
|
|---|
| 137 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
|
|---|
| 138 | StochasticBranch stochasticBranchCrossover = new StochasticBranch();
|
|---|
| 139 | Placeholder crossover = new Placeholder();
|
|---|
| 140 | StochasticBranch stochasticBranchMutator = new StochasticBranch();
|
|---|
| 141 | Placeholder mutator = new Placeholder();
|
|---|
| 142 | Placeholder specialStages = new Placeholder();
|
|---|
| 143 | SubScopesRemover subScopesRemover = new SubScopesRemover();
|
|---|
| 144 | UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
|
|---|
| 145 | Placeholder evaluator = new Placeholder();
|
|---|
| 146 | SubScopesCounter subScopesCounter = new SubScopesCounter();
|
|---|
| 147 | SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
|
|---|
| 148 | BestSelector bestSelector = new BestSelector();
|
|---|
| 149 | RightReducer rightReducer = new RightReducer();
|
|---|
| 150 | MergingReducer mergingReducer = new MergingReducer();
|
|---|
| 151 | IntCounter intCounter = new IntCounter();
|
|---|
| 152 | Comparator comparator = new Comparator();
|
|---|
| 153 | Placeholder analyzer2 = new Placeholder();
|
|---|
| 154 | ConditionalBranch conditionalBranch = new ConditionalBranch();
|
|---|
| 155 |
|
|---|
| 156 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
|
|---|
| 157 |
|
|---|
| 158 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
|
|---|
| 159 | resultsCollector1.ResultsParameter.ActualName = "Results";
|
|---|
| 160 |
|
|---|
| 161 | analyzer1.Name = "Analyzer";
|
|---|
| 162 | analyzer1.OperatorParameter.ActualName = "Analyzer";
|
|---|
| 163 |
|
|---|
| 164 | selector.Name = "Selector";
|
|---|
| 165 | selector.OperatorParameter.ActualName = "Selector";
|
|---|
| 166 |
|
|---|
| 167 | childrenCreator.ParentsPerChild = new IntValue(2);
|
|---|
| 168 |
|
|---|
| 169 | stochasticBranchCrossover.ProbabilityParameter.ActualName = "CrossoverProbability";
|
|---|
| 170 | stochasticBranchCrossover.RandomParameter.ActualName = "Random";
|
|---|
| 171 |
|
|---|
| 172 | crossover.Name = "Crossover";
|
|---|
| 173 | crossover.OperatorParameter.ActualName = "Crossover";
|
|---|
| 174 |
|
|---|
| 175 | stochasticBranchMutator.ProbabilityParameter.ActualName = "MutationProbability";
|
|---|
| 176 | stochasticBranchMutator.RandomParameter.ActualName = "Random";
|
|---|
| 177 |
|
|---|
| 178 | mutator.Name = "Mutator";
|
|---|
| 179 | mutator.OperatorParameter.ActualName = "Mutator";
|
|---|
| 180 |
|
|---|
| 181 | specialStages.Name = "SpecialStages";
|
|---|
| 182 | specialStages.OperatorParameter.ActualName = "SpecialStages";
|
|---|
| 183 |
|
|---|
| 184 | subScopesRemover.RemoveAllSubScopes = true;
|
|---|
| 185 |
|
|---|
| 186 | uniformSubScopesProcessor2.Parallel.Value = true;
|
|---|
| 187 |
|
|---|
| 188 | evaluator.Name = "Evaluator";
|
|---|
| 189 | evaluator.OperatorParameter.ActualName = "Evaluator";
|
|---|
| 190 |
|
|---|
| 191 | subScopesCounter.Name = "Increment EvaluatedSolutions";
|
|---|
| 192 | subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
|
|---|
| 193 |
|
|---|
| 194 | bestSelector.CopySelected = new BoolValue(false);
|
|---|
| 195 | bestSelector.MaximizationParameter.ActualName = "Maximization";
|
|---|
| 196 | bestSelector.NumberOfSelectedSubScopesParameter.ActualName = "Elites";
|
|---|
| 197 | bestSelector.QualityParameter.ActualName = "Quality";
|
|---|
| 198 |
|
|---|
| 199 | intCounter.Increment = new IntValue(1);
|
|---|
| 200 | intCounter.ValueParameter.ActualName = "Generations";
|
|---|
| 201 |
|
|---|
| 202 | comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
|
|---|
| 203 | comparator.LeftSideParameter.ActualName = "Generations";
|
|---|
| 204 | comparator.ResultParameter.ActualName = "Terminate";
|
|---|
| 205 | comparator.RightSideParameter.ActualName = "MaximumGenerations";
|
|---|
| 206 |
|
|---|
| 207 | analyzer2.Name = "Analyzer";
|
|---|
| 208 | analyzer2.OperatorParameter.ActualName = "Analyzer";
|
|---|
| 209 |
|
|---|
| 210 | conditionalBranch.ConditionParameter.ActualName = "Terminate";
|
|---|
| 211 | #endregion
|
|---|
| 212 |
|
|---|
| 213 | #region Create operator graph
|
|---|
| 214 | OperatorGraph.InitialOperator = variableCreator;
|
|---|
| 215 | variableCreator.Successor = resultsCollector1;
|
|---|
| 216 | resultsCollector1.Successor = analyzer1;
|
|---|
| 217 | analyzer1.Successor = selector;
|
|---|
| 218 | selector.Successor = subScopesProcessor1;
|
|---|
| 219 | subScopesProcessor1.Operators.Add(new EmptyOperator());
|
|---|
| 220 | subScopesProcessor1.Operators.Add(childrenCreator);
|
|---|
| 221 | subScopesProcessor1.Successor = subScopesProcessor2;
|
|---|
| 222 | childrenCreator.Successor = uniformSubScopesProcessor1;
|
|---|
| 223 | uniformSubScopesProcessor1.Operator = stochasticBranchCrossover;
|
|---|
| 224 | uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
|
|---|
| 225 | stochasticBranchCrossover.FirstBranch = crossover;
|
|---|
| 226 | stochasticBranchCrossover.SecondBranch = null;
|
|---|
| 227 | stochasticBranchCrossover.Successor = stochasticBranchMutator;
|
|---|
| 228 | crossover.Successor = null;
|
|---|
| 229 | stochasticBranchMutator.FirstBranch = mutator;
|
|---|
| 230 | stochasticBranchMutator.SecondBranch = null;
|
|---|
| 231 | stochasticBranchMutator.Successor = specialStages;
|
|---|
| 232 | mutator.Successor = null;
|
|---|
| 233 | specialStages.Successor = subScopesRemover;
|
|---|
| 234 | subScopesRemover.Successor = null;
|
|---|
| 235 | uniformSubScopesProcessor2.Operator = evaluator;
|
|---|
| 236 | uniformSubScopesProcessor2.Successor = subScopesCounter;
|
|---|
| 237 | evaluator.Successor = null;
|
|---|
| 238 | subScopesCounter.Successor = null;
|
|---|
| 239 | subScopesProcessor2.Operators.Add(bestSelector);
|
|---|
| 240 | subScopesProcessor2.Operators.Add(new EmptyOperator());
|
|---|
| 241 | subScopesProcessor2.Successor = mergingReducer;
|
|---|
| 242 | bestSelector.Successor = rightReducer;
|
|---|
| 243 | rightReducer.Successor = null;
|
|---|
| 244 | mergingReducer.Successor = intCounter;
|
|---|
| 245 | intCounter.Successor = comparator;
|
|---|
| 246 | comparator.Successor = analyzer2;
|
|---|
| 247 | analyzer2.Successor = conditionalBranch;
|
|---|
| 248 | conditionalBranch.FalseBranch = selector;
|
|---|
| 249 | conditionalBranch.TrueBranch = null;
|
|---|
| 250 | conditionalBranch.Successor = null;
|
|---|
| 251 | #endregion
|
|---|
| 252 | }
|
|---|
| 253 |
|
|---|
| 254 | public override IOperation Apply() {
|
|---|
| 255 | if (CrossoverParameter.ActualValue == null)
|
|---|
| 256 | return null;
|
|---|
| 257 | return base.Apply();
|
|---|
| 258 | }
|
|---|
| 259 | }
|
|---|
| 260 | }
|
|---|
