#region License Information /* HeuristicLab * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using HeuristicLab.Analysis; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Optimization.Operators; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.Selection; namespace HeuristicLab.Algorithms.SGA { /// /// An operator which represents the main loop of a standard genetic algorithm (SGA). /// [Item("SGAMainLoop", "An operator which represents the main loop of a standard genetic algorithm (SGA).")] [Creatable("Test")] [StorableClass] public sealed class SGAMainLoop : AlgorithmOperator { #region Parameter properties public ValueLookupParameter RandomParameter { get { return (ValueLookupParameter)Parameters["Random"]; } } public ValueLookupParameter MaximizationParameter { get { return (ValueLookupParameter)Parameters["Maximization"]; } } public SubScopesLookupParameter QualityParameter { get { return (SubScopesLookupParameter)Parameters["Quality"]; } } public ValueLookupParameter BestKnownQualityParameter { get { return (ValueLookupParameter)Parameters["BestKnownQuality"]; } } public ValueLookupParameter SelectorParameter { get { return (ValueLookupParameter)Parameters["Selector"]; } } public ValueLookupParameter CrossoverParameter { get { return (ValueLookupParameter)Parameters["Crossover"]; } } public ValueLookupParameter MutationProbabilityParameter { get { return (ValueLookupParameter)Parameters["MutationProbability"]; } } public ValueLookupParameter MutatorParameter { get { return (ValueLookupParameter)Parameters["Mutator"]; } } public ValueLookupParameter EvaluatorParameter { get { return (ValueLookupParameter)Parameters["Evaluator"]; } } public ValueLookupParameter ElitesParameter { get { return (ValueLookupParameter)Parameters["Elites"]; } } public ValueLookupParameter MaximumGenerationsParameter { get { return (ValueLookupParameter)Parameters["MaximumGenerations"]; } } public ValueLookupParameter ResultsParameter { get { return (ValueLookupParameter)Parameters["Results"]; } } public ValueLookupParameter VisualizerParameter { get { return (ValueLookupParameter)Parameters["Visualizer"]; } } public LookupParameter VisualizationParameter { get { return (LookupParameter)Parameters["Visualization"]; } } private ScopeParameter CurrentScopeParameter { get { return (ScopeParameter)Parameters["CurrentScope"]; } } public IScope CurrentScope { get { return CurrentScopeParameter.ActualValue; } } #endregion [StorableConstructor] private SGAMainLoop(bool deserializing) : base() { } public SGAMainLoop() : base() { Initialize(); } private void Initialize() { #region Create parameters Parameters.Add(new ValueLookupParameter("Random", "A pseudo random number generator.")); Parameters.Add(new ValueLookupParameter("Maximization", "True if the problem is a maximization problem, otherwise false.")); Parameters.Add(new SubScopesLookupParameter("Quality", "The value which represents the quality of a solution.")); Parameters.Add(new ValueLookupParameter("BestKnownQuality", "The best known quality value found so far.")); Parameters.Add(new ValueLookupParameter("Selector", "The operator used to select solutions for reproduction.")); Parameters.Add(new ValueLookupParameter("Crossover", "The operator used to cross solutions.")); Parameters.Add(new ValueLookupParameter("MutationProbability", "The probability that the mutation operator is applied on a solution.")); Parameters.Add(new ValueLookupParameter("Mutator", "The operator used to mutate solutions.")); Parameters.Add(new ValueLookupParameter("Evaluator", "The operator used to evaluate solutions.")); Parameters.Add(new ValueLookupParameter("Elites", "The numer of elite solutions which are kept in each generation.")); Parameters.Add(new ValueLookupParameter("MaximumGenerations", "The maximum number of generations which should be processed.")); Parameters.Add(new ValueLookupParameter("Results", "The variable collection where results should be stored.")); Parameters.Add(new ValueLookupParameter("Visualizer", "The operator used to visualize solutions.")); Parameters.Add(new LookupParameter("Visualization", "The item which represents the visualization of solutions.")); Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the SGA should be applied.")); #endregion #region Create operators VariableCreator variableCreator = new VariableCreator(); BestQualityMemorizer bestQualityMemorizer1 = new BestQualityMemorizer(); BestQualityMemorizer bestQualityMemorizer2 = new BestQualityMemorizer(); BestAverageWorstQualityCalculator bestAverageWorstQualityCalculator1 = new BestAverageWorstQualityCalculator(); DataTableValuesCollector dataTableValuesCollector1 = new DataTableValuesCollector(); QualityDifferenceCalculator qualityDifferenceCalculator1 = new QualityDifferenceCalculator(); Placeholder visualizer1 = new Placeholder(); ResultsCollector resultsCollector = new ResultsCollector(); Placeholder selector = new Placeholder(); SequentialSubScopesProcessor sequentialSubScopesProcessor1 = new SequentialSubScopesProcessor(); ChildrenCreator childrenCreator = new ChildrenCreator(); UniformSequentialSubScopesProcessor uniformSequentialSubScopesProcessor = new UniformSequentialSubScopesProcessor(); Placeholder crossover = new Placeholder(); StochasticBranch stochasticBranch = new StochasticBranch(); Placeholder mutator = new Placeholder(); Placeholder evaluator = new Placeholder(); SubScopesRemover subScopesRemover = new SubScopesRemover(); SequentialSubScopesProcessor sequentialSubScopesProcessor2 = new SequentialSubScopesProcessor(); BestSelector bestSelector = new BestSelector(); RightReducer rightReducer = new RightReducer(); MergingReducer mergingReducer = new MergingReducer(); IntCounter intCounter = new IntCounter(); Comparator comparator = new Comparator(); BestQualityMemorizer bestQualityMemorizer3 = new BestQualityMemorizer(); BestQualityMemorizer bestQualityMemorizer4 = new BestQualityMemorizer(); BestAverageWorstQualityCalculator bestAverageWorstQualityCalculator2 = new BestAverageWorstQualityCalculator(); DataTableValuesCollector dataTableValuesCollector2 = new DataTableValuesCollector(); QualityDifferenceCalculator qualityDifferenceCalculator2 = new QualityDifferenceCalculator(); Placeholder visualizer2 = new Placeholder(); ConditionalBranch conditionalBranch = new ConditionalBranch(); variableCreator.CollectedValues.Add(new ValueParameter("Generations", new IntValue(0))); bestQualityMemorizer1.BestQualityParameter.ActualName = "BestQuality"; bestQualityMemorizer1.MaximizationParameter.ActualName = "Maximization"; bestQualityMemorizer1.QualityParameter.ActualName = "Quality"; bestQualityMemorizer2.BestQualityParameter.ActualName = "BestKnownQuality"; bestQualityMemorizer2.MaximizationParameter.ActualName = "Maximization"; bestQualityMemorizer2.QualityParameter.ActualName = "Quality"; bestAverageWorstQualityCalculator1.AverageQualityParameter.ActualName = "CurrentAverageQuality"; bestAverageWorstQualityCalculator1.BestQualityParameter.ActualName = "CurrentBestQuality"; bestAverageWorstQualityCalculator1.MaximizationParameter.ActualName = "Maximization"; bestAverageWorstQualityCalculator1.QualityParameter.ActualName = "Quality"; bestAverageWorstQualityCalculator1.WorstQualityParameter.ActualName = "CurrentWorstQuality"; dataTableValuesCollector1.CollectedValues.Add(new LookupParameter("Current Best Quality", null, "CurrentBestQuality")); dataTableValuesCollector1.CollectedValues.Add(new LookupParameter("Current Average Quality", null, "CurrentAverageQuality")); dataTableValuesCollector1.CollectedValues.Add(new LookupParameter("Current Worst Quality", null, "CurrentWorstQuality")); dataTableValuesCollector1.CollectedValues.Add(new LookupParameter("Best Quality", null, "BestQuality")); dataTableValuesCollector1.CollectedValues.Add(new LookupParameter("Best Known Quality", null, "BestKnownQuality")); dataTableValuesCollector1.DataTableParameter.ActualName = "Qualities"; qualityDifferenceCalculator1.AbsoluteDifferenceParameter.ActualName = "AbsoluteDifferenceBestKnownToBest"; qualityDifferenceCalculator1.FirstQualityParameter.ActualName = "BestKnownQuality"; qualityDifferenceCalculator1.RelativeDifferenceParameter.ActualName = "RelativeDifferenceBestKnownToBest"; qualityDifferenceCalculator1.SecondQualityParameter.ActualName = "BestQuality"; visualizer1.Name = "Visualizer"; visualizer1.OperatorParameter.ActualName = "Visualizer"; resultsCollector.CollectedValues.Add(new LookupParameter("Generations")); resultsCollector.CollectedValues.Add(new LookupParameter("Current Best Quality", null, "CurrentBestQuality")); resultsCollector.CollectedValues.Add(new LookupParameter("Current Average Quality", null, "CurrentAverageQuality")); resultsCollector.CollectedValues.Add(new LookupParameter("Current Worst Quality", null, "CurrentWorstQuality")); resultsCollector.CollectedValues.Add(new LookupParameter("Best Quality", null, "BestQuality")); resultsCollector.CollectedValues.Add(new LookupParameter("Best Known Quality", null, "BestKnownQuality")); resultsCollector.CollectedValues.Add(new LookupParameter("Absolute Difference of Best Known Quality to Best Quality", null, "AbsoluteDifferenceBestKnownToBest")); resultsCollector.CollectedValues.Add(new LookupParameter("Relative Difference of Best Known Quality to Best Quality", null, "RelativeDifferenceBestKnownToBest")); resultsCollector.CollectedValues.Add(new LookupParameter("Solution Visualization", null, "Visualization")); resultsCollector.CollectedValues.Add(new LookupParameter("Qualities")); resultsCollector.ResultsParameter.ActualName = "Results"; selector.Name = "Selector"; selector.OperatorParameter.ActualName = "Selector"; childrenCreator.ParentsPerChild = new IntValue(2); crossover.Name = "Crossover"; crossover.OperatorParameter.ActualName = "Crossover"; stochasticBranch.ProbabilityParameter.ActualName = "MutationProbability"; stochasticBranch.RandomParameter.ActualName = "Random"; mutator.Name = "Mutator"; mutator.OperatorParameter.ActualName = "Mutator"; evaluator.Name = "Evaluator"; evaluator.OperatorParameter.ActualName = "Evaluator"; subScopesRemover.RemoveAllSubScopes = true; bestSelector.CopySelected = new BoolValue(false); bestSelector.MaximizationParameter.ActualName = "Maximization"; bestSelector.NumberOfSelectedSubScopesParameter.ActualName = "Elites"; bestSelector.QualityParameter.ActualName = "Quality"; intCounter.Increment = new IntValue(1); intCounter.ValueParameter.ActualName = "Generations"; comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual); comparator.LeftSideParameter.ActualName = "Generations"; comparator.ResultParameter.ActualName = "Terminate"; comparator.RightSideParameter.ActualName = "MaximumGenerations"; bestQualityMemorizer3.BestQualityParameter.ActualName = "BestQuality"; bestQualityMemorizer3.MaximizationParameter.ActualName = "Maximization"; bestQualityMemorizer3.QualityParameter.ActualName = "Quality"; bestQualityMemorizer4.BestQualityParameter.ActualName = "BestKnownQuality"; bestQualityMemorizer4.MaximizationParameter.ActualName = "Maximization"; bestQualityMemorizer4.QualityParameter.ActualName = "Quality"; bestAverageWorstQualityCalculator2.AverageQualityParameter.ActualName = "CurrentAverageQuality"; bestAverageWorstQualityCalculator2.BestQualityParameter.ActualName = "CurrentBestQuality"; bestAverageWorstQualityCalculator2.MaximizationParameter.ActualName = "Maximization"; bestAverageWorstQualityCalculator2.QualityParameter.ActualName = "Quality"; bestAverageWorstQualityCalculator2.WorstQualityParameter.ActualName = "CurrentWorstQuality"; dataTableValuesCollector2.CollectedValues.Add(new LookupParameter("Current Best Quality", null, "CurrentBestQuality")); dataTableValuesCollector2.CollectedValues.Add(new LookupParameter("Current Average Quality", null, "CurrentAverageQuality")); dataTableValuesCollector2.CollectedValues.Add(new LookupParameter("Current Worst Quality", null, "CurrentWorstQuality")); dataTableValuesCollector2.CollectedValues.Add(new LookupParameter("Best Quality", null, "BestQuality")); dataTableValuesCollector2.CollectedValues.Add(new LookupParameter("Best Known Quality", null, "BestKnownQuality")); dataTableValuesCollector2.DataTableParameter.ActualName = "Qualities"; qualityDifferenceCalculator2.AbsoluteDifferenceParameter.ActualName = "AbsoluteDifferenceBestKnownToBest"; qualityDifferenceCalculator2.FirstQualityParameter.ActualName = "BestKnownQuality"; qualityDifferenceCalculator2.RelativeDifferenceParameter.ActualName = "RelativeDifferenceBestKnownToBest"; qualityDifferenceCalculator2.SecondQualityParameter.ActualName = "BestQuality"; visualizer2.Name = "Visualizer"; visualizer2.OperatorParameter.ActualName = "Visualizer"; conditionalBranch.ConditionParameter.ActualName = "Terminate"; #endregion #region Create operator graph OperatorGraph.InitialOperator = variableCreator; variableCreator.Successor = bestQualityMemorizer1; bestQualityMemorizer1.Successor = bestQualityMemorizer2; bestQualityMemorizer2.Successor = bestAverageWorstQualityCalculator1; bestAverageWorstQualityCalculator1.Successor = dataTableValuesCollector1; dataTableValuesCollector1.Successor = qualityDifferenceCalculator1; qualityDifferenceCalculator1.Successor = visualizer1; visualizer1.Successor = resultsCollector; resultsCollector.Successor = selector; selector.Successor = sequentialSubScopesProcessor1; sequentialSubScopesProcessor1.Operators.Add(new EmptyOperator()); sequentialSubScopesProcessor1.Operators.Add(childrenCreator); sequentialSubScopesProcessor1.Successor = sequentialSubScopesProcessor2; childrenCreator.Successor = uniformSequentialSubScopesProcessor; uniformSequentialSubScopesProcessor.Operator = crossover; uniformSequentialSubScopesProcessor.Successor = null; crossover.Successor = stochasticBranch; stochasticBranch.FirstBranch = mutator; stochasticBranch.SecondBranch = null; stochasticBranch.Successor = evaluator; mutator.Successor = null; evaluator.Successor = subScopesRemover; subScopesRemover.Successor = null; sequentialSubScopesProcessor2.Operators.Add(bestSelector); sequentialSubScopesProcessor2.Operators.Add(new EmptyOperator()); sequentialSubScopesProcessor2.Successor = mergingReducer; bestSelector.Successor = rightReducer; rightReducer.Successor = null; mergingReducer.Successor = intCounter; intCounter.Successor = comparator; comparator.Successor = bestQualityMemorizer3; bestQualityMemorizer3.Successor = bestQualityMemorizer4; bestQualityMemorizer4.Successor = bestAverageWorstQualityCalculator2; bestAverageWorstQualityCalculator2.Successor = dataTableValuesCollector2; dataTableValuesCollector2.Successor = qualityDifferenceCalculator2; qualityDifferenceCalculator2.Successor = visualizer2; visualizer2.Successor = conditionalBranch; conditionalBranch.FalseBranch = selector; conditionalBranch.TrueBranch = null; conditionalBranch.Successor = null; #endregion } } }