Changeset 12120 for branches/ALPS/HeuristicLab.Algorithms.ALPS.SteadyState/3.3/AlpsSsGeneticAlgorithm.cs

Timestamp:

03/04/15 14:07:38 (9 years ago)

Author:

pfleck

Message:

#2350

• Implemented AlpsSsGeneticAlgorithm.
• Created empty AlpsSsGeneticAlgorithmMainLoop.

File:

• branches/ALPS/HeuristicLab.Algorithms.ALPS.SteadyState/3.3/AlpsSsGeneticAlgorithm.cs (modified) (3 diffs)

branches/ALPS/HeuristicLab.Algorithms.ALPS.SteadyState/3.3/AlpsSsGeneticAlgorithm.cs

@@ -21 +21 @@
 
 using System;
+using System.Linq;
 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.Default.CompositeSerializers.Storable;
+using HeuristicLab.PluginInfrastructure;
+using HeuristicLab.Random;
+using HeuristicLab.Selection;
 
 namespace HeuristicLab.Algorithms.ALPS.SteadyState {
@@ -34 +40 @@
   public class AlpsSsGeneticAlgorithm : Alps {
     #region Parameter Properties
-    // TODO
+    private IValueParameter<IntArray> PopulationSizeParameter {
+      get { return (IValueParameter<IntArray>)Parameters["PopulationSize"]; }
+    }
+    private IValueParameter<IntValue> MaximumGenerationsParameter {
+      get { return (IValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
+    }
+    public IConstrainedValueParameter<ISelector> SelectorParameter {
+      get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
+    }
+    public IConstrainedValueParameter<ICrossover> CrossoverParameter {
+      get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
+    }
+    private IValueParameter<PercentValue> MutationProbabilityParameter {
+      get { return (IValueParameter<PercentValue>)Parameters["MutationProbability"]; }
+    }
+    public IConstrainedValueParameter<IManipulator> MutatorParameter {
+      get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
+    }
+    private IValueParameter<IntValue> ElitesParameter {
+      get { return (IValueParameter<IntValue>)Parameters["Elites"]; }
+    }
+    private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
+    }
     #endregion
 
     #region Properties
-    // TODO
+    public IntArray PopulationSize {
+      get { return PopulationSizeParameter.Value; }
+      set { PopulationSizeParameter.Value = value; }
+    }
+    public IntValue MaximumGenerations {
+      get { return MaximumGenerationsParameter.Value; }
+      set { MaximumGenerationsParameter.Value = value; }
+    }
+
+    public ISelector Selector {
+      get { return SelectorParameter.Value; }
+      set { SelectorParameter.Value = value; }
+    }
+    public ICrossover Crossover {
+      get { return CrossoverParameter.Value; }
+      set { CrossoverParameter.Value = value; }
+    }
+    public PercentValue MutationProbability {
+      get { return MutationProbabilityParameter.Value; }
+      set { MutationProbabilityParameter.Value = value; }
+    }
+    public IManipulator Mutator {
+      get { return MutatorParameter.Value; }
+      set { MutatorParameter.Value = value; }
+    }
+    public IntValue Elites {
+      get { return ElitesParameter.Value; }
+      set { ElitesParameter.Value = value; }
+    }
+    public bool ReevaluteElites {
+      get { return ReevaluateElitesParameter.Value.Value; }
+      set { ReevaluateElitesParameter.Value.Value = value; }
+    }
     #endregion
 
@@ -54 +115 @@
     public AlpsSsGeneticAlgorithm()
       : base() {
-
-      // TODO
-
+      Parameters.Add(new ValueParameter<IntArray>("PopulationSize", "The size of the population of solutions each layer.", new IntArray(new[] { 100 })));
+      Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
+      Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
+      Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
+      Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
+      Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
+      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
+      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 });
+      AgeInheritance = new ReductionOperation(ReductionOperations.Min);
+
+      var randomCreator = new RandomCreator();
+      var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
+      var layer0Processor = new LayerUniformSubScopesProcessor();
+      var layer0VariableCreator = new VariableCreator();
+      var layer0SolutionsCreator = new SolutionsCreator();
+      var initializeAgeProcessor = new UniformSubScopesProcessor();
+      var initializeAge = new VariableCreator() { Name = "Initialize Age" };
+      var initializeLocalEvaluatedSolutions = new SubScopesCounter() { Name = "Initialize LayerEvaluatedSolutions" };
+      var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
+      var resultsCollector = new ResultsCollector();
+      var mainLoop = new AlpsSsGeneticAlgorithmMainLoop();
+
+      OperatorGraph.InitialOperator = randomCreator;
+
+      randomCreator.SeedParameter.Value = null;
+      randomCreator.SetSeedRandomlyParameter.Value = null;
+      randomCreator.Successor = layer0Creator;
+
+      layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
+      layer0Creator.Successor = layer0Processor;
+
+      layer0Processor.Operator = layer0VariableCreator;
+      layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
+
+      layer0VariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Layer", new IntValue(0)));
+      layer0VariableCreator.Successor = layer0SolutionsCreator;
+
+      layer0SolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
+      layer0SolutionsCreator.Successor = initializeAgeProcessor;
+
+      initializeAgeProcessor.Operator = initializeAge;
+      initializeAgeProcessor.Successor = initializeLocalEvaluatedSolutions;
+
+      initializeAge.CollectedValues.Add(new ValueParameter<IntValue>("Age", new IntValue(0)));
+
+      initializeLocalEvaluatedSolutions.ValueParameter.ActualName = "LayerEvaluatedSolutions";
+
+      initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
+      initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
+      initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
+      initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
+      initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
+
+      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
+      resultsCollector.Successor = mainLoop;
+
+      foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
+        SelectorParameter.ValidValues.Add(selector);
+      var tournamentSelector = SelectorParameter.ValidValues.OfType<TournamentSelector>().FirstOrDefault();
+      if (tournamentSelector != null) {
+        tournamentSelector.GroupSizeParameter.Value = new IntValue(5);
+        SelectorParameter.Value = tournamentSelector;
+      }
+
+      ParameterizeSelectors();
       Initialize();
     }
 
     #region Events
+    protected override void OnProblemChanged() {
+      base.OnProblemChanged();
+      ParameterizeSolutionsCreator();
+      ParameterizeMainLoop();
+      ParameterizeSelectors();
+      ParameterizeIterationBasedOperators();
+      UpdateCrossovers();
+      UpdateMutators();
+    }
+    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
+      base.Problem_SolutionCreatorChanged(sender, e);
+      ParameterizeSolutionsCreator();
+    }
+    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
+      base.Problem_EvaluatorChanged(sender, e);
+      ParameterizeSolutionsCreator();
+      ParameterizeMainLoop();
+      ParameterizeSelectors();
+    }
+    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
+      base.Problem_OperatorsChanged(sender, e);
+      ParameterizeIterationBasedOperators();
+      UpdateCrossovers();
+      UpdateMutators();
+    }
+    protected override void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
+      base.Evaluator_QualityParameter_ActualNameChanged(sender, e);
+      ParameterizeMainLoop();
+      ParameterizeSelectors();
+    }
     #endregion
 
     #region Parameterization
     private void Initialize() {
-      // TODO
-    }
+      //
+    }
+    private void ParameterizeSolutionsCreator() {
+      //MainLoop.LayerUpdator.SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
+      //MainLoop.LayerUpdator.SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
+    }
+    private void ParameterizeMainLoop() {
+      //MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
+      //MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
+      //MainLoop.MainOperator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
+      //MainLoop.MainOperator.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
+      //MainLoop.MainOperator.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
+      //MainLoop.LayerUpdator.SolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
+    }
+    private void ParameterizeSelectors() {
+      foreach (var selector in SelectorParameter.ValidValues) {
+        selector.CopySelected = new BoolValue(true);
+        // Explicit setting of NumberOfSelectedSubScopesParameter is not required anymore because the NumberOfSelectedSubScopesCalculator calculates it itself
+        //selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSize - Elites.Value)); 
+        selector.NumberOfSelectedSubScopesParameter.Hidden = true;
+        ParameterizeStochasticOperatorForLayer(selector);
+      }
+      if (Problem != null) {
+        foreach (var selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
+          selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
+          selector.MaximizationParameter.Hidden = true;
+          selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
+          selector.QualityParameter.Hidden = true;
+        }
+      }
+    }
+    private void ParameterizeIterationBasedOperators() {
+      if (Problem != null) {
+        foreach (var @operator in Problem.Operators.OfType<IIterationBasedOperator>()) {
+          @operator.IterationsParameter.ActualName = "Generations";
+          @operator.IterationsParameter.Hidden = true;
+          @operator.MaximumIterationsParameter.ActualName = MaximumGenerationsParameter.Name;
+          @operator.MaximumIterationsParameter.Hidden = true;
+        }
+      }
+    }
+
+    protected override void ParameterizeStochasticOperatorForLayer(IOperator @operator) {
+      var stochasticOperator = @operator as IStochasticOperator;
+      if (stochasticOperator != null) {
+        stochasticOperator.RandomParameter.ActualName = GlobalRandomCreator.Name;
+        stochasticOperator.RandomParameter.Hidden = true;
+      }
+    }
+
     #endregion
 
     #region Updates
+    private void UpdateCrossovers() {
+      var oldCrossover = CrossoverParameter.Value;
+      var defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
+      CrossoverParameter.ValidValues.Clear();
+      foreach (var crossover in Problem.Operators.OfType<ICrossover>().OrderBy(c => c.Name)) {
+        ParameterizeStochasticOperatorForLayer(crossover);
+        CrossoverParameter.ValidValues.Add(crossover);
+      }
+      if (oldCrossover != null) {
+        var crossover = CrossoverParameter.ValidValues.FirstOrDefault(c => c.GetType() == oldCrossover.GetType());
+        if (crossover != null)
+          CrossoverParameter.Value = crossover;
+        else
+          oldCrossover = null;
+      }
+      if (oldCrossover == null && defaultCrossover != null)
+        CrossoverParameter.Value = defaultCrossover;
+    }
+    private void UpdateMutators() {
+      var oldMutator = MutatorParameter.Value;
+      MutatorParameter.ValidValues.Clear();
+      foreach (var mutator in Problem.Operators.OfType<IManipulator>().OrderBy(m => m.Name)) {
+        ParameterizeStochasticOperatorForLayer(mutator);
+        MutatorParameter.ValidValues.Add(mutator);
+      }
+      if (oldMutator != null) {
+        var mutator = MutatorParameter.ValidValues.FirstOrDefault(m => m.GetType() == oldMutator.GetType());
+        if (mutator != null)
+          MutatorParameter.Value = mutator;
+      }
+    }
     #endregion
   }