Changeset 9553 for trunk/sources

Timestamp:

05/29/13 13:14:58 (11 years ago)

Author:

mkommend

Message:

#2038: Added possibility to reevaluate elites in the GA.

Location:

trunk/sources/HeuristicLab.Algorithms.GeneticAlgorithm/3.3

Files:

• GeneticAlgorithm.cs (modified) (4 diffs)
• GeneticAlgorithmMainLoop.cs (modified) (6 diffs)

trunk/sources/HeuristicLab.Algorithms.GeneticAlgorithm/3.3/GeneticAlgorithm.cs

@@ -79 +79 @@
       get { return (ValueParameter<IntValue>)Parameters["Elites"]; }
     }
+    private IFixedValueParameter<BoolValue> ReevaluateElitesParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters["ReevaluateElites"]; }
+    }
     private ValueParameter<MultiAnalyzer> AnalyzerParameter {
       get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
@@ -119 +122 @@
       get { return ElitesParameter.Value; }
       set { ElitesParameter.Value = value; }
+    }
+    public bool ReevaluteElites {
+      get { return ReevaluateElitesParameter.Value.Value; }
+      set { ReevaluateElitesParameter.Value.Value = value; }
     }
     public MultiAnalyzer Analyzer {
@@ -151 +158 @@
       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 });
       Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
       Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed.", new IntValue(1000)));
@@ -207 +215 @@
     [StorableHook(HookType.AfterDeserialization)]
     private void AfterDeserialization() {
+      if (!Parameters.ContainsKey("ReevaluateElites")) {
+        Parameters.Add(new FixedValueParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", (BoolValue)new BoolValue(false).AsReadOnly()) { Hidden = true });
+      }
       Initialize();
     }

trunk/sources/HeuristicLab.Algorithms.GeneticAlgorithm/3.3/GeneticAlgorithmMainLoop.cs

@@ -63 +63 @@
     public ValueLookupParameter<IntValue> ElitesParameter {
       get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
+    }
+    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
+      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
     }
     public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
@@ -112 +115 @@
       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."));
       Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
+      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
       Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
       Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
@@ -143 +147 @@
       Placeholder analyzer2 = new Placeholder();
       ConditionalBranch conditionalBranch = new ConditionalBranch();
+      ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
+      UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
+      Placeholder evaluator2 = new Placeholder();
+      SubScopesCounter subScopesCounter2 = new SubScopesCounter();
 
       variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
@@ -193 +201 @@
 
       conditionalBranch.ConditionParameter.ActualName = "Terminate";
+
+      reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
+      reevaluateElitesBranch.Name = "Reevaluate elites ?";
+
+      uniformSubScopesProcessor3.Parallel.Value = true;
+
+      evaluator2.Name = "Evaluator";
+      evaluator2.OperatorParameter.ActualName = "Evaluator";
+
+      subScopesCounter2.Name = "Increment EvaluatedSolutions";
+      subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
+
       #endregion
 
@@ -221 +241 @@
       subScopesProcessor2.Successor = mergingReducer;
       bestSelector.Successor = rightReducer;
-      rightReducer.Successor = null;
+      rightReducer.Successor = reevaluateElitesBranch;
+      reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor3;
+      uniformSubScopesProcessor3.Operator = evaluator;
+      uniformSubScopesProcessor3.Successor = subScopesCounter2;
+      reevaluateElitesBranch.FalseBranch = null;
+      reevaluateElitesBranch.Successor = null;
       mergingReducer.Successor = intCounter;
       intCounter.Successor = comparator;
@@ -232 +257 @@
     }
 
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      if (!Parameters.ContainsKey("ReevaluateElites")) {
+        Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
+      }
+    }
+
     public override IOperation Apply() {
       if (CrossoverParameter.ActualValue == null)