Changeset 15238 for stable/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm

Timestamp:

07/13/17 17:46:58 (7 years ago)

Author:

mkommend

Message:

#2792: Merged r15006:r15008, r15047, r15049, r15070, r15107 into stable.

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/IslandOffspringSelectionGeneticAlgorithm.cs (modified) (3 diffs)
• HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/OffspringSelectionGeneticAlgorithm.cs (modified) (3 diffs)
• HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/SASEGASA.cs (modified) (3 diffs)

stable/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/IslandOffspringSelectionGeneticAlgorithm.cs

@@ -280 +280 @@
       if (!Parameters.ContainsKey("FillPopulationWithParents"))
         Parameters.Add(new FixedValueParameter<BoolValue>("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.", new BoolValue(false)) { Hidden = true });
+
+      var optionalMutatorParameter = MutatorParameter as OptionalConstrainedValueParameter<IManipulator>;
+      if (optionalMutatorParameter != null) {
+        Parameters.Remove(optionalMutatorParameter);
+        Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
+        foreach (var m in optionalMutatorParameter.ValidValues)
+          MutatorParameter.ValidValues.Add(m);
+        if (optionalMutatorParameter.Value == null) MutationProbability.Value = 0; // to guarantee that the old configuration results in the same behavior
+        else Mutator = optionalMutatorParameter.Value;
+        optionalMutatorParameter.ValidValues.Clear(); // to avoid dangling references to the old parameter its valid values are cleared
+      }
       #endregion
 
@@ -311 +322 @@
       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 ConstrainedValueParameter<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 });
@@ -642 +653 @@
       IManipulator oldMutator = MutatorParameter.Value;
       MutatorParameter.ValidValues.Clear();
+      IManipulator defaultMutator = Problem.Operators.OfType<IManipulator>().FirstOrDefault();
+
       foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
         MutatorParameter.ValidValues.Add(mutator);
+
       if (oldMutator != null) {
         IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
         if (mutator != null) MutatorParameter.Value = mutator;
-      }
+        else oldMutator = null;
+      }
+
+      if (oldMutator == null && defaultMutator != null)
+        MutatorParameter.Value = defaultMutator;
     }
     private void UpdateAnalyzers() {

stable/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/OffspringSelectionGeneticAlgorithm.cs

@@ -228 +228 @@
       if (!Parameters.ContainsKey("FillPopulationWithParents"))
         Parameters.Add(new FixedValueParameter<BoolValue>("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.", new BoolValue(false)) { Hidden = true });
+
+      var optionalMutatorParameter = MutatorParameter as OptionalConstrainedValueParameter<IManipulator>;
+      if (optionalMutatorParameter != null) {
+        Parameters.Remove(optionalMutatorParameter);
+        Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
+        foreach (var m in optionalMutatorParameter.ValidValues)
+          MutatorParameter.ValidValues.Add(m);
+        if (optionalMutatorParameter.Value == null) MutationProbability.Value = 0; // to guarantee that the old configuration results in the same behavior
+        else Mutator = optionalMutatorParameter.Value;
+        optionalMutatorParameter.ValidValues.Clear(); // to avoid dangling references to the old parameter its valid values are cleared
+      }
       #endregion
 
@@ -250 +261 @@
       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 ConstrainedValueParameter<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 });
@@ -487 +498 @@
       IManipulator oldMutator = MutatorParameter.Value;
       MutatorParameter.ValidValues.Clear();
+      IManipulator defaultMutator = Problem.Operators.OfType<IManipulator>().FirstOrDefault();
+
       foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
         MutatorParameter.ValidValues.Add(mutator);
+
       if (oldMutator != null) {
         IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
         if (mutator != null) MutatorParameter.Value = mutator;
-      }
+        else oldMutator = null;
+      }
+
+      if (oldMutator == null && defaultMutator != null)
+        MutatorParameter.Value = defaultMutator;
     }
     private void UpdateAnalyzers() {

stable/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/SASEGASA.cs

@@ -256 +256 @@
       if (!Parameters.ContainsKey("FillPopulationWithParents"))
         Parameters.Add(new FixedValueParameter<BoolValue>("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.", new BoolValue(false)) { Hidden = true });
+
+      var optionalMutatorParameter = MutatorParameter as OptionalConstrainedValueParameter<IManipulator>;
+      if (optionalMutatorParameter != null) {
+        Parameters.Remove(optionalMutatorParameter);
+        Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
+        foreach (var m in optionalMutatorParameter.ValidValues)
+          MutatorParameter.ValidValues.Add(m);
+        if (optionalMutatorParameter.Value == null) MutationProbability.Value = 0; // to guarantee that the old configuration results in the same behavior
+        else Mutator = optionalMutatorParameter.Value;
+        optionalMutatorParameter.ValidValues.Clear(); // to avoid dangling references to the old parameter its valid values are cleared
+      }
       #endregion
 
@@ -282 +293 @@
       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 ConstrainedValueParameter<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 });
@@ -561 +572 @@
       ICrossover oldCrossover = CrossoverParameter.Value;
       CrossoverParameter.ValidValues.Clear();
+      ICrossover defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
+
       foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
         CrossoverParameter.ValidValues.Add(crossover);
+
       if (oldCrossover != null) {
         ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
         if (crossover != null) CrossoverParameter.Value = crossover;
-      }
+        else oldCrossover = null;
+      }
+      if (oldCrossover == null && defaultCrossover != null)
+        CrossoverParameter.Value = defaultCrossover;
     }
     private void UpdateMutators() {
       IManipulator oldMutator = MutatorParameter.Value;
       MutatorParameter.ValidValues.Clear();
+      IManipulator defaultMutator = Problem.Operators.OfType<IManipulator>().FirstOrDefault();
+
       foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
         MutatorParameter.ValidValues.Add(mutator);
+
       if (oldMutator != null) {
         IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
         if (mutator != null) MutatorParameter.Value = mutator;
-      }
+        else oldMutator = null;
+      }
+
+      if (oldMutator == null && defaultMutator != null)
+        MutatorParameter.Value = defaultMutator;
     }
     private void UpdateAnalyzers() {