Changeset 5576 for branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test

Timestamp:

03/01/11 10:25:48 (13 years ago)

Author:

cneumuel

Message:

#1215

• implemented best solution history analyzer
• implemented quality analyzer for each base-level problem

File:

• branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test/Program.cs (modified) (4 diffs)

branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test/Program.cs

@@ -48 +48 @@
     //private static int baseAlgorithmMaxGenerations = 1000;
 
-    private static int metaAlgorithmPopulationSize = 20;
-    private static int metaAlgorithmMaxGenerations = 20;
+    private static int metaAlgorithmPopulationSize = 5;
+    private static int metaAlgorithmMaxGenerations = 15;
     private static int metaProblemRepetitions = 2;
-    private static int baseAlgorithmMaxGenerations = 10;
+    private static int baseAlgorithmMaxGenerations = 5;
     private static double mutationProbability = 0.10;
 
@@ -638 +638 @@
         ProblemSize = new IntValue(2)
       });
-      //metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
-      //  Evaluator = new GriewankEvaluator(),
-      //  ProblemSize = new IntValue(20)
-      //});
-      //metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
-      //  Evaluator = new GriewankEvaluator(),
-      //  ProblemSize = new IntValue(500)
-      //});
-
-      ConfigurePopulationSize(algorithmVc, 0, 20, 1);
+      metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
+        Evaluator = new GriewankEvaluator(),
+        ProblemSize = new IntValue(20)
+      });
+      metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
+        Evaluator = new GriewankEvaluator(),
+        ProblemSize = new IntValue(500)
+      });
+
+      ConfigurePopulationSize(algorithmVc, 5, 20, 1);
       ConfigureMutationRate(algorithmVc, 0.0, 1.0, 0.01);
       ConfigureMutationOperator(algorithmVc);
-      ConfigureElites(algorithmVc, 0, 30, 1);
+      //ConfigureElites(algorithmVc, 0, 30, 1);
       ConfigureSelectionOperator(algorithmVc, true);
       return algorithmVc;
@@ -855 +855 @@
                 var orderedRuns = rc.OrderBy(x => x.Results["AverageQualityNormalized"]);
 
-                TableBuilder tb = new TableBuilder("QNorm", "Qualities", "PoSi", "MutRa", "Eli", "SelOp", "MutOp", "NrSelSubScopes");
+                TableBuilder tb = new TableBuilder("QNorm", "Qualities", "PoSi", "MutRa", /*"Eli",*/ "SelOp", "MutOp", "NrSelSubScopes");
                 foreach (IRun run in orderedRuns) {
                   string selector;
@@ -869 +869 @@
                     ((IntValue)run.Parameters["PopulationSize"]).Value.ToString(),
                     ((DoubleValue)run.Parameters["MutationProbability"]).Value.ToString("0.0000"),
-                    ((IntValue)run.Parameters["Elites"]).Value.ToString(),
+                    //((IntValue)run.Parameters["Elites"]).Value.ToString(),
                     Shorten(selector, 20),
                     Shorten(run.Parameters.ContainsKey("Mutator") ? run.Parameters["Mutator"].ToString() : "null", 40),