Changeset 5277 for branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test/Program.cs

Timestamp:

01/11/11 16:00:17 (13 years ago)

Author:

cneumuel

Message:

#1215

• implemented crossover and manipulator operators for int and double values

File:

• branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test/Program.cs (modified) (13 diffs)

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

@@ -31 +31 @@
     //private static int baseAlgorithmMaxGenerations = 1000;
 
-    private static int metaAlgorithmPopulationSize = 10;
+    private static int metaAlgorithmPopulationSize = 16;
     private static int metaAlgorithmMaxGenerations = 20;
     private static int metaProblemRepetitions = 3;
-    private static int baseAlgorithmMaxGenerations = 10;
+    private static int baseAlgorithmMaxGenerations = 50;
 
     static void Main(string[] args) {
@@ -54 +54 @@
       //TestWaitAny();
       //TestExecutionTimeUpdateInvervalPerformance();
-      TestMemoryConsumption();
-      return;
+      //TestMemoryConsumption();
 
       GeneticAlgorithm baseLevelAlgorithm = new GeneticAlgorithm();
@@ -61 +60 @@
       MetaOptimizationProblem metaOptimizationProblem = new MetaOptimizationProblem();
       metaOptimizationProblem.Repetitions = new IntValue(metaProblemRepetitions);
-      GeneticAlgorithm metaLevelAlgorithm = GetMetaGA(metaOptimizationProblem);
-      //GeneticAlgorithm metaLevelAlgorithm = GetParallelMetaGA(metaOptimizationProblem);
+      //GeneticAlgorithm metaLevelAlgorithm = GetMetaGA(metaOptimizationProblem);
+      GeneticAlgorithm metaLevelAlgorithm = GetParallelMetaGA(metaOptimizationProblem);
       //GeneticAlgorithm metaLevelAlgorithm = GetHiveParallelMetaGA(metaOptimizationProblem);
 
@@ -106 +105 @@
         algs.Add(clonedGa);
         sw.Reset();
-        ContentManager.Save((IStorableContent)metaLevelAlgorithm, "alg_"+i+".hl", true);
+        ContentManager.Save((IStorableContent)metaLevelAlgorithm, "alg_" + i + ".hl", true);
         Console.WriteLine("Cloned alg #{0}", i);
       }
@@ -119 +118 @@
       RepeatExecuteParallel(3, 1, 1, tb);
       tb.AppendRow("--", "--", "--", "--", "--", "--", "--", "--", "--");
-      RepeatExecuteParallel(repetitions, tasks, 1, tb); 
-      RepeatExecuteParallel(repetitions, tasks, 2.5, tb); 
+      RepeatExecuteParallel(repetitions, tasks, 1, tb);
+      RepeatExecuteParallel(repetitions, tasks, 2.5, tb);
       RepeatExecuteParallel(repetitions, tasks, 5, tb);
       RepeatExecuteParallel(repetitions, tasks, 10, tb);
       RepeatExecuteParallel(repetitions, tasks, 25, tb);
       RepeatExecuteParallel(repetitions, tasks, 50, tb);
-      RepeatExecuteParallel(repetitions, tasks, 100, tb); 
-      RepeatExecuteParallel(repetitions, tasks, 250, tb); 
-      RepeatExecuteParallel(repetitions, tasks, 500, tb); 
+      RepeatExecuteParallel(repetitions, tasks, 100, tb);
+      RepeatExecuteParallel(repetitions, tasks, 250, tb);
+      RepeatExecuteParallel(repetitions, tasks, 500, tb);
       RepeatExecuteParallel(repetitions, tasks, 1000, tb);
-      RepeatExecuteParallel(repetitions, tasks, 2500, tb);     
+      RepeatExecuteParallel(repetitions, tasks, 2500, tb);
       RepeatExecuteParallel(repetitions, tasks, 5000, tb);
 
@@ -148 +147 @@
     private static void RepeatExecuteParallel(int repetitions, int tasks, double executionTimeUpdateIntervalMs, TableBuilder tb) {
       for (int i = 0; i < repetitions; i++) {
-        ExecuteParallel(tasks, executionTimeUpdateIntervalMs, tb); 
-        Console.Clear(); 
+        ExecuteParallel(tasks, executionTimeUpdateIntervalMs, tb);
+        Console.Clear();
         Console.WriteLine(tb.ToString());
       }
@@ -167 +166 @@
         tasks[i] = new Task<TimeSpan>((alg) => {
           Console.WriteLine("Task {0} started.", Task.CurrentId);
-          
+
           Stopwatch swx = new Stopwatch();
           swx.Start();
@@ -197 +196 @@
         double totalMilliseconds = tasks.Select(t => t.Result.TotalMilliseconds).Sum();
         tb.AppendRow(
-          taskCount.ToString(), 
-          executionTimeUpdateIntervalMs.ToString(), 
+          taskCount.ToString(),
+          executionTimeUpdateIntervalMs.ToString(),
           TimeSpan.FromMilliseconds(totalExecutionTimeMilliseconds).ToString(),
-          TimeSpan.FromMilliseconds(totalExecutionTimeMilliseconds / taskCount).ToString(), 
+          TimeSpan.FromMilliseconds(totalExecutionTimeMilliseconds / taskCount).ToString(),
           sw.Elapsed.ToString(),
           TimeSpan.FromMilliseconds(totalMilliseconds).ToString(),
           (totalMilliseconds / sw.ElapsedMilliseconds).ToString("0.00"),
           counter.ToString(),
-          (totalExecutionTimeMilliseconds/counter).ToString("0.00"));
+          (totalExecutionTimeMilliseconds / counter).ToString("0.00"));
       }
       tasks = null;
@@ -510 +509 @@
       ParameterConfigurationTree algorithmVc = metaOptimizationProblem.ParameterConfigurationTree;
 
-      metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
-        Evaluator = new GriewankEvaluator(),
-        ProblemSize = new IntValue(5)
-      });
-      metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
-        Evaluator = new GriewankEvaluator(),
-        ProblemSize = new IntValue(50)
-      });
+      //metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
+      //  Evaluator = new GriewankEvaluator(),
+      //  ProblemSize = new IntValue(5)
+      //});
+      //metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
+      //  Evaluator = new GriewankEvaluator(),
+      //  ProblemSize = new IntValue(50)
+      //});
       metaOptimizationProblem.Problems.Add(new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() {
         Evaluator = new GriewankEvaluator(),
@@ -526 +525 @@
       ConfigureMutationRate(algorithmVc, 0.0, 1.0, 0.01);
       ConfigureMutationOperator(algorithmVc);
-      ConfigureElites(algorithmVc, 0, 10, 1);
-      ConfigureSelectionOperator(algorithmVc, true);
+      //ConfigureElites(algorithmVc, 0, 10, 1);
+      //ConfigureSelectionOperator(algorithmVc, true);
       return algorithmVc;
     }
@@ -554 +553 @@
         IValueConfiguration clonedVc = (IValueConfiguration)algorithmVc.Clone();
         GeneticAlgorithm newAlg = (GeneticAlgorithm)baseLevelAlgorithm.Clone();
-        //clonedVc.Mutate(rand);
-
-        //.Apply(rand, clonedVc); todo
+        ParameterConfigurationManipulator.Apply(rand, clonedVc, new UniformIntValueManipulator(), new NormalDoubleValueManipulator());
         clonedVc.Parameterize(newAlg);
+
         Console.WriteLine(string.Format("PopSize: original: {0}, mutated: {1}", baseLevelAlgorithm.PopulationSize, newAlg.PopulationSize));
         Console.WriteLine(string.Format("MutRate: original: {0}, mutated: {1}", baseLevelAlgorithm.MutationProbability, newAlg.MutationProbability));
@@ -588 +586 @@
 
         //clonedVc1.Cross(clonedVc2, rand); todo
+
+        ParameterConfigurationCrossover.Apply(rand, clonedVc1, clonedVc2, new DiscreteIntValueCrossover(), new AverageDoubleValueCrossover());
         clonedVc1.Parameterize(first);
 
@@ -706 +706 @@
         int currentGeneration = -1;
         do {
-          Thread.Sleep(500);
+          Thread.Sleep(1000);
           if (metaLevelAlgorithm.Results.ContainsKey("Generations") && ((IntValue)metaLevelAlgorithm.Results["Generations"].Value).Value != currentGeneration) {
             while (metaLevelAlgorithm.Results.Count < 3) Thread.Sleep(100);