#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Optimization; using HeuristicLab.Optimization.Operators; using HeuristicLab.Parameters; using HeuristicLab.Persistence; namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm { /// /// An island offspring selection genetic algorithm main loop operator. /// [Item("IslandOffspringSelectionGeneticAlgorithmMainLoop", "An island offspring selection genetic algorithm main loop operator.")] [StorableType("04fac72b-a80d-4aab-93a7-12de987e37f6")] public sealed class IslandOffspringSelectionGeneticAlgorithmMainLoop : AlgorithmOperator { #region Parameter Properties public ValueLookupParameter RandomParameter { get { return (ValueLookupParameter)Parameters["Random"]; } } public ValueLookupParameter MaximizationParameter { get { return (ValueLookupParameter)Parameters["Maximization"]; } } public ScopeTreeLookupParameter QualityParameter { get { return (ScopeTreeLookupParameter)Parameters["Quality"]; } } public ValueLookupParameter BestKnownQualityParameter { get { return (ValueLookupParameter)Parameters["BestKnownQuality"]; } } public ValueLookupParameter NumberOfIslandsParameter { get { return (ValueLookupParameter)Parameters["NumberOfIslands"]; } } public ValueLookupParameter MigrationIntervalParameter { get { return (ValueLookupParameter)Parameters["MigrationInterval"]; } } public ValueLookupParameter MigrationRateParameter { get { return (ValueLookupParameter)Parameters["MigrationRate"]; } } public ValueLookupParameter MigratorParameter { get { return (ValueLookupParameter)Parameters["Migrator"]; } } public ValueLookupParameter EmigrantsSelectorParameter { get { return (ValueLookupParameter)Parameters["EmigrantsSelector"]; } } public ValueLookupParameter ImmigrationReplacerParameter { get { return (ValueLookupParameter)Parameters["ImmigrationReplacer"]; } } public ValueLookupParameter PopulationSizeParameter { get { return (ValueLookupParameter)Parameters["PopulationSize"]; } } public ValueLookupParameter MaximumGenerationsParameter { get { return (ValueLookupParameter)Parameters["MaximumGenerations"]; } } 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 IValueLookupParameter ReevaluateElitesParameter { get { return (IValueLookupParameter)Parameters["ReevaluateElites"]; } } public ValueLookupParameter ResultsParameter { get { return (ValueLookupParameter)Parameters["Results"]; } } public ValueLookupParameter VisualizerParameter { get { return (ValueLookupParameter)Parameters["Visualizer"]; } } public LookupParameter VisualizationParameter { get { return (LookupParameter)Parameters["Visualization"]; } } public ValueLookupParameter SuccessRatioParameter { get { return (ValueLookupParameter)Parameters["SuccessRatio"]; } } public LookupParameter ComparisonFactorParameter { get { return (LookupParameter)Parameters["ComparisonFactor"]; } } public ValueLookupParameter ComparisonFactorStartParameter { get { return (ValueLookupParameter)Parameters["ComparisonFactorStart"]; } } public ValueLookupParameter ComparisonFactorModifierParameter { get { return (ValueLookupParameter)Parameters["ComparisonFactorModifier"]; } } public ValueLookupParameter MaximumSelectionPressureParameter { get { return (ValueLookupParameter)Parameters["MaximumSelectionPressure"]; } } public ValueLookupParameter OffspringSelectionBeforeMutationParameter { get { return (ValueLookupParameter)Parameters["OffspringSelectionBeforeMutation"]; } } public ValueLookupParameter AnalyzerParameter { get { return (ValueLookupParameter)Parameters["Analyzer"]; } } public ValueLookupParameter IslandAnalyzerParameter { get { return (ValueLookupParameter)Parameters["IslandAnalyzer"]; } } public LookupParameter EvaluatedSolutionsParameter { get { return (LookupParameter)Parameters["EvaluatedSolutions"]; } } public IValueLookupParameter FillPopulationWithParentsParameter { get { return (IValueLookupParameter)Parameters["FillPopulationWithParents"]; } } #endregion [StorableConstructor] private IslandOffspringSelectionGeneticAlgorithmMainLoop(StorableConstructorFlag deserializing) : base(deserializing) { } private IslandOffspringSelectionGeneticAlgorithmMainLoop(IslandOffspringSelectionGeneticAlgorithmMainLoop original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new IslandOffspringSelectionGeneticAlgorithmMainLoop(this, cloner); } public IslandOffspringSelectionGeneticAlgorithmMainLoop() : base() { #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 ScopeTreeLookupParameter("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("NumberOfIslands", "The number of islands.")); Parameters.Add(new ValueLookupParameter("MigrationInterval", "The number of generations that should pass between migration phases.")); Parameters.Add(new ValueLookupParameter("MigrationRate", "The proportion of individuals that should migrate between the islands.")); Parameters.Add(new ValueLookupParameter("Migrator", "The migration strategy.")); Parameters.Add(new ValueLookupParameter("EmigrantsSelector", "Selects the individuals that will be migrated.")); Parameters.Add(new ValueLookupParameter("ImmigrationReplacer", "Replaces part of the original population with the immigrants.")); Parameters.Add(new ValueLookupParameter("PopulationSize", "The size of the population of solutions.")); Parameters.Add(new ValueLookupParameter("MaximumGenerations", "The maximum number of generations that should be processed.")); 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. This operator is executed in parallel, if an engine is used which supports parallelization.")); Parameters.Add(new ValueLookupParameter("Elites", "The numer of elite solutions which are kept in each generation.")); Parameters.Add(new ValueLookupParameter("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)")); Parameters.Add(new ValueLookupParameter("Results", "The results collection to store the results.")); 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 ValueLookupParameter("SuccessRatio", "The ratio of successful to total children that should be achieved.")); Parameters.Add(new LookupParameter("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1].")); Parameters.Add(new ValueLookupParameter("ComparisonFactorStart", "The initial value for the comparison factor.")); Parameters.Add(new ValueLookupParameter("ComparisonFactorModifier", "The operator used to modify the comparison factor.")); Parameters.Add(new ValueLookupParameter("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm.")); Parameters.Add(new ValueLookupParameter("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation.")); Parameters.Add(new ValueLookupParameter("Analyzer", "The operator used to the analyze the islands.")); Parameters.Add(new ValueLookupParameter("IslandAnalyzer", "The operator used to analyze each island.")); Parameters.Add(new LookupParameter("EvaluatedSolutions", "The number of times solutions have been evaluated.")); Parameters.Add(new ValueLookupParameter("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded.")); #endregion #region Create operators VariableCreator variableCreator = new VariableCreator(); UniformSubScopesProcessor uniformSubScopesProcessor0 = new UniformSubScopesProcessor(); VariableCreator islandVariableCreator = new VariableCreator(); Placeholder islandAnalyzer1 = new Placeholder(); ResultsCollector islandResultsCollector1 = new ResultsCollector(); Assigner comparisonFactorInitializer = new Assigner(); Placeholder analyzer1 = new Placeholder(); ResultsCollector resultsCollector1 = new ResultsCollector(); UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor(); ConditionalBranch islandTerminatedBySelectionPressure1 = new ConditionalBranch(); OffspringSelectionGeneticAlgorithmMainOperator mainOperator = new OffspringSelectionGeneticAlgorithmMainOperator(); Placeholder islandAnalyzer2 = new Placeholder(); ResultsCollector islandResultsCollector2 = new ResultsCollector(); Comparator islandSelectionPressureComparator = new Comparator(); ConditionalBranch islandTerminatedBySelectionPressure2 = new ConditionalBranch(); IntCounter terminatedIslandsCounter = new IntCounter(); IntCounter generationsCounter = new IntCounter(); IntCounter generationsSinceLastMigrationCounter = new IntCounter(); Comparator migrationComparator = new Comparator(); ConditionalBranch migrationBranch = new ConditionalBranch(); Assigner resetTerminatedIslandsAssigner = new Assigner(); Assigner resetGenerationsSinceLastMigrationAssigner = new Assigner(); IntCounter migrationsCounter = new IntCounter(); UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor(); Assigner reviveIslandAssigner = new Assigner(); Placeholder emigrantsSelector = new Placeholder(); Placeholder migrator = new Placeholder(); UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor(); Placeholder immigrationReplacer = new Placeholder(); Comparator generationsComparator = new Comparator(); Comparator terminatedIslandsComparator = new Comparator(); Comparator maxEvaluatedSolutionsComparator = new Comparator(); Placeholder comparisonFactorModifier = new Placeholder(); Placeholder analyzer2 = new Placeholder(); ConditionalBranch generationsTerminationCondition = new ConditionalBranch(); ConditionalBranch terminatedIslandsCondition = new ConditionalBranch(); ConditionalBranch evaluatedSolutionsTerminationCondition = new ConditionalBranch(); variableCreator.CollectedValues.Add(new ValueParameter("Migrations", new IntValue(0))); variableCreator.CollectedValues.Add(new ValueParameter("Generations", new IntValue(0))); // Class IslandOffspringSelectionGeneticAlgorithm expects this to be called Generations variableCreator.CollectedValues.Add(new ValueParameter("GenerationsSinceLastMigration", new IntValue(0))); variableCreator.CollectedValues.Add(new ValueParameter("TerminatedIslands", new IntValue(0))); islandVariableCreator.CollectedValues.Add(new ValueParameter(ResultsParameter.Name, new ResultCollection())); islandVariableCreator.CollectedValues.Add(new ValueParameter("TerminateSelectionPressure", new BoolValue(false))); islandVariableCreator.CollectedValues.Add(new ValueParameter("SelectionPressure", new DoubleValue(0))); islandAnalyzer1.Name = "Island Analyzer (placeholder)"; islandAnalyzer1.OperatorParameter.ActualName = IslandAnalyzerParameter.Name; islandResultsCollector1.CollectedValues.Add(new LookupParameter("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure")); islandResultsCollector1.CollectedValues.Add(new LookupParameter("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio")); islandResultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name; comparisonFactorInitializer.Name = "Initialize Comparison Factor"; comparisonFactorInitializer.LeftSideParameter.ActualName = ComparisonFactorParameter.Name; comparisonFactorInitializer.RightSideParameter.ActualName = ComparisonFactorStartParameter.Name; analyzer1.Name = "Analyzer (placeholder)"; analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name; resultsCollector1.CopyValue = new BoolValue(false); resultsCollector1.CollectedValues.Add(new LookupParameter("Migrations")); resultsCollector1.CollectedValues.Add(new LookupParameter("Generations")); resultsCollector1.CollectedValues.Add(new LookupParameter("Current Comparison Factor", null, ComparisonFactorParameter.Name)); resultsCollector1.CollectedValues.Add(new ScopeTreeLookupParameter("IslandResults", "Result set for each island", ResultsParameter.Name)); resultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name; islandTerminatedBySelectionPressure1.Name = "Island Terminated ?"; islandTerminatedBySelectionPressure1.ConditionParameter.ActualName = "TerminateSelectionPressure"; mainOperator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name; mainOperator.CrossoverParameter.ActualName = CrossoverParameter.Name; mainOperator.CurrentSuccessRatioParameter.ActualName = "CurrentSuccessRatio"; mainOperator.ElitesParameter.ActualName = ElitesParameter.Name; mainOperator.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name; mainOperator.EvaluatedSolutionsParameter.ActualName = EvaluatedSolutionsParameter.Name; mainOperator.EvaluatorParameter.ActualName = EvaluatorParameter.Name; mainOperator.MaximizationParameter.ActualName = MaximizationParameter.Name; mainOperator.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name; mainOperator.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name; mainOperator.MutatorParameter.ActualName = MutatorParameter.Name; mainOperator.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name; mainOperator.QualityParameter.ActualName = QualityParameter.Name; mainOperator.RandomParameter.ActualName = RandomParameter.Name; mainOperator.SelectionPressureParameter.ActualName = "SelectionPressure"; mainOperator.SelectorParameter.ActualName = SelectorParameter.Name; mainOperator.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name; mainOperator.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name; islandAnalyzer2.Name = "Island Analyzer (placeholder)"; islandAnalyzer2.OperatorParameter.ActualName = IslandAnalyzerParameter.Name; islandResultsCollector2.CollectedValues.Add(new LookupParameter("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure")); islandResultsCollector2.CollectedValues.Add(new LookupParameter("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio")); islandResultsCollector2.ResultsParameter.ActualName = "Results"; islandSelectionPressureComparator.Name = "SelectionPressure >= MaximumSelectionPressure ?"; islandSelectionPressureComparator.LeftSideParameter.ActualName = "SelectionPressure"; islandSelectionPressureComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual); islandSelectionPressureComparator.RightSideParameter.ActualName = MaximumSelectionPressureParameter.Name; islandSelectionPressureComparator.ResultParameter.ActualName = "TerminateSelectionPressure"; islandTerminatedBySelectionPressure2.Name = "Island Terminated ?"; islandTerminatedBySelectionPressure2.ConditionParameter.ActualName = "TerminateSelectionPressure"; terminatedIslandsCounter.Name = "TerminatedIslands + 1"; terminatedIslandsCounter.ValueParameter.ActualName = "TerminatedIslands"; terminatedIslandsCounter.Increment = new IntValue(1); generationsCounter.Name = "Generations + 1"; generationsCounter.ValueParameter.ActualName = "Generations"; generationsCounter.Increment = new IntValue(1); generationsSinceLastMigrationCounter.Name = "GenerationsSinceLastMigration + 1"; generationsSinceLastMigrationCounter.ValueParameter.ActualName = "GenerationsSinceLastMigration"; generationsSinceLastMigrationCounter.Increment = new IntValue(1); migrationComparator.Name = "GenerationsSinceLastMigration = MigrationInterval ?"; migrationComparator.LeftSideParameter.ActualName = "GenerationsSinceLastMigration"; migrationComparator.Comparison = new Comparison(ComparisonType.Equal); migrationComparator.RightSideParameter.ActualName = MigrationIntervalParameter.Name; migrationComparator.ResultParameter.ActualName = "Migrate"; migrationBranch.Name = "Migrate?"; migrationBranch.ConditionParameter.ActualName = "Migrate"; resetTerminatedIslandsAssigner.Name = "Reset TerminatedIslands"; resetTerminatedIslandsAssigner.LeftSideParameter.ActualName = "TerminatedIslands"; resetTerminatedIslandsAssigner.RightSideParameter.Value = new IntValue(0); resetGenerationsSinceLastMigrationAssigner.Name = "Reset GenerationsSinceLastMigration"; resetGenerationsSinceLastMigrationAssigner.LeftSideParameter.ActualName = "GenerationsSinceLastMigration"; resetGenerationsSinceLastMigrationAssigner.RightSideParameter.Value = new IntValue(0); migrationsCounter.Name = "Migrations + 1"; migrationsCounter.IncrementParameter.Value = new IntValue(1); migrationsCounter.ValueParameter.ActualName = "Migrations"; reviveIslandAssigner.Name = "Revive Island"; reviveIslandAssigner.LeftSideParameter.ActualName = "TerminateSelectionPressure"; reviveIslandAssigner.RightSideParameter.Value = new BoolValue(false); emigrantsSelector.Name = "Emigrants Selector (placeholder)"; emigrantsSelector.OperatorParameter.ActualName = EmigrantsSelectorParameter.Name; migrator.Name = "Migrator (placeholder)"; migrator.OperatorParameter.ActualName = MigratorParameter.Name; immigrationReplacer.Name = "Immigration Replacer (placeholder)"; immigrationReplacer.OperatorParameter.ActualName = ImmigrationReplacerParameter.Name; generationsComparator.Name = "Generations >= MaximumGenerations ?"; generationsComparator.LeftSideParameter.ActualName = "Generations"; generationsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual); generationsComparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name; generationsComparator.ResultParameter.ActualName = "TerminateGenerations"; terminatedIslandsComparator.Name = "All Islands terminated ?"; terminatedIslandsComparator.LeftSideParameter.ActualName = "TerminatedIslands"; terminatedIslandsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual); terminatedIslandsComparator.RightSideParameter.ActualName = NumberOfIslandsParameter.Name; terminatedIslandsComparator.ResultParameter.ActualName = "TerminateTerminatedIslands"; maxEvaluatedSolutionsComparator.Name = "EvaluatedSolutions >= MaximumEvaluatedSolutions ?"; maxEvaluatedSolutionsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual); maxEvaluatedSolutionsComparator.LeftSideParameter.ActualName = EvaluatedSolutionsParameter.Name; maxEvaluatedSolutionsComparator.ResultParameter.ActualName = "TerminateEvaluatedSolutions"; maxEvaluatedSolutionsComparator.RightSideParameter.ActualName = "MaximumEvaluatedSolutions"; comparisonFactorModifier.Name = "Update Comparison Factor (Placeholder)"; comparisonFactorModifier.OperatorParameter.ActualName = ComparisonFactorModifierParameter.Name; analyzer2.Name = "Analyzer (placeholder)"; analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name; generationsTerminationCondition.Name = "Terminate (MaxGenerations) ?"; generationsTerminationCondition.ConditionParameter.ActualName = "TerminateGenerations"; terminatedIslandsCondition.Name = "Terminate (TerminatedIslands) ?"; terminatedIslandsCondition.ConditionParameter.ActualName = "TerminateTerminatedIslands"; evaluatedSolutionsTerminationCondition.Name = "Terminate (EvaluatedSolutions) ?"; evaluatedSolutionsTerminationCondition.ConditionParameter.ActualName = "TerminateEvaluatedSolutions"; #endregion #region Create operator graph OperatorGraph.InitialOperator = variableCreator; variableCreator.Successor = uniformSubScopesProcessor0; uniformSubScopesProcessor0.Operator = islandVariableCreator; uniformSubScopesProcessor0.Successor = comparisonFactorInitializer; islandVariableCreator.Successor = islandAnalyzer1; islandAnalyzer1.Successor = islandResultsCollector1; islandResultsCollector1.Successor = null; comparisonFactorInitializer.Successor = analyzer1; analyzer1.Successor = resultsCollector1; resultsCollector1.Successor = uniformSubScopesProcessor1; uniformSubScopesProcessor1.Operator = islandTerminatedBySelectionPressure1; uniformSubScopesProcessor1.Successor = generationsCounter; islandTerminatedBySelectionPressure1.TrueBranch = null; islandTerminatedBySelectionPressure1.FalseBranch = mainOperator; islandTerminatedBySelectionPressure1.Successor = null; mainOperator.Successor = islandAnalyzer2; islandAnalyzer2.Successor = islandResultsCollector2; islandResultsCollector2.Successor = islandSelectionPressureComparator; islandSelectionPressureComparator.Successor = islandTerminatedBySelectionPressure2; islandTerminatedBySelectionPressure2.TrueBranch = terminatedIslandsCounter; islandTerminatedBySelectionPressure2.FalseBranch = null; islandTerminatedBySelectionPressure2.Successor = null; generationsCounter.Successor = generationsSinceLastMigrationCounter; generationsSinceLastMigrationCounter.Successor = migrationComparator; migrationComparator.Successor = migrationBranch; migrationBranch.TrueBranch = resetTerminatedIslandsAssigner; migrationBranch.FalseBranch = null; migrationBranch.Successor = generationsComparator; resetTerminatedIslandsAssigner.Successor = resetGenerationsSinceLastMigrationAssigner; resetGenerationsSinceLastMigrationAssigner.Successor = migrationsCounter; migrationsCounter.Successor = uniformSubScopesProcessor2; uniformSubScopesProcessor2.Operator = reviveIslandAssigner; uniformSubScopesProcessor2.Successor = migrator; reviveIslandAssigner.Successor = emigrantsSelector; emigrantsSelector.Successor = null; migrator.Successor = uniformSubScopesProcessor3; uniformSubScopesProcessor3.Operator = immigrationReplacer; uniformSubScopesProcessor3.Successor = null; immigrationReplacer.Successor = null; generationsComparator.Successor = terminatedIslandsComparator; terminatedIslandsComparator.Successor = maxEvaluatedSolutionsComparator; maxEvaluatedSolutionsComparator.Successor = comparisonFactorModifier; comparisonFactorModifier.Successor = analyzer2; analyzer2.Successor = generationsTerminationCondition; generationsTerminationCondition.TrueBranch = null; generationsTerminationCondition.FalseBranch = terminatedIslandsCondition; generationsTerminationCondition.Successor = null; terminatedIslandsCondition.TrueBranch = null; terminatedIslandsCondition.FalseBranch = evaluatedSolutionsTerminationCondition; terminatedIslandsCondition.Successor = null; evaluatedSolutionsTerminationCondition.TrueBranch = null; evaluatedSolutionsTerminationCondition.FalseBranch = uniformSubScopesProcessor1; evaluatedSolutionsTerminationCondition.Successor = null; #endregion } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { // BackwardsCompatibility3.3 #region Backwards compatible code, remove with 3.4 if (!Parameters.ContainsKey("ReevaluateElites")) { Parameters.Add(new ValueLookupParameter("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)")); } if (!Parameters.ContainsKey("FillPopulationWithParents")) Parameters.Add(new ValueLookupParameter("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded.")); #endregion } public override IOperation Apply() { if (CrossoverParameter.ActualValue == null) return null; return base.Apply(); } } }