Changeset 14690 for branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape

Timestamp:

02/20/17 20:41:33 (8 years ago)

Author:

abeham

Message:

#2457: working on identification of problem instances

Location:

branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3

Files:

• CharacteristicCalculator/RandomWalkCalculator.cs (modified) (2 diffs)
• ProblemCharacteristicAnalysis/QAP/QAPDirectedWalk.cs (modified) (7 diffs)

branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3/CharacteristicCalculator/RandomWalkCalculator.cs

@@ -58 +58 @@
       characteristics = cloner.Clone(original.characteristics);
     }
-    public RandomWalkCalculator() {
+    public RandomWalkCalculator() : this(new RandomWalk()) { }
+    public RandomWalkCalculator(RandomWalk walker) {
       Name = ItemName;
       Description = ItemDescription;
-      walker = new RandomWalk();
+      this.walker = walker;
       characteristics = new CheckedItemList<StringValue>(
         new[] { "AutoCorrelation1", "CorrelationLength", "InformationContent",
-        "PartialInformationContent", "DensityBasinInformation", "InformationStability", 
+        "PartialInformationContent", "DensityBasinInformation", "InformationStability",
         "Diversity", "Regularity", "TotalEntropy", "PeakInformationContent",
         "PeakDensityBasinInformation" }.Select(x => new StringValue(x)));
@@ -91 +92 @@
         };
         walker.ExecutionStateChanged += evHandle;
-        walker.Start();
-        waitHandle.WaitOne();
-        walker.ExecutionStateChanged -= evHandle;
+        try {
+          walker.Start();
+          waitHandle.WaitOne();
+        } finally { walker.ExecutionStateChanged -= evHandle; }
       }
       foreach (var p in characteristics.CheckedItems) {
-        yield return new Result("RandomWalk." + walker.MutatorParameter.Value.Name + "." + p.Value.Value, walker.Results[p.Value.Value].Value);
+        var resultName = "RandomWalk." + walker.MutatorParameter.Value.Name + "." + p.Value.Value;
+        IResult result;
+        if (walker.Results.TryGetValue(p.Value.Value, out result)) {
+          yield return new Result(resultName, result.Value);
+        } else yield return new Result(resultName, new DoubleValue(0));
       }
       walker.Prepare(true);

branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3/ProblemCharacteristicAnalysis/QAP/QAPDirectedWalk.cs

@@ -32 +32 @@
 using System.Collections.Generic;
 using System.Linq;
+using System.Threading;
 
 namespace HeuristicLab.Analysis.FitnessLandscape {
@@ -50 +51 @@
     }
 
+    public IFixedValueParameter<BoolValue> LocalOptimaParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters["LocalOptima"]; }
+    }
+
     public int Paths {
       get { return PathsParameter.Value.Value; }
@@ -63 +68 @@
       get { return SeedParameter.Value != null ? SeedParameter.Value.Value : (int?)null; }
       set { SeedParameter.Value = value.HasValue ? new IntValue(value.Value) : null; }
+    }
+
+    public bool LocalOptima {
+      get { return LocalOptimaParameter.Value.Value; }
+      set { LocalOptimaParameter.Value.Value = value; }
     }
 
@@ -74 +84 @@
       Parameters.Add(new FixedValueParameter<BoolValue>("BestImprovement", "Whether the best of all alternatives should be chosen for each step in the path or just the first improving (least degrading) move should be made.", new BoolValue(true)));
       Parameters.Add(new OptionalValueParameter<IntValue>("Seed", "The seed for the random number generator."));
+      Parameters.Add(new FixedValueParameter<BoolValue>("LocalOptima", "Whether to perform walks between local optima.", new BoolValue(false)));
     }
 
@@ -90 +101 @@
 
       var perm = new Permutation(PermutationTypes.Absolute, qap.Weights.Rows, random);
+      if (LocalOptima) {
+        var fit = new DoubleValue(QAPEvaluator.Apply(perm, qap.Weights, qap.Distances));
+        QAPExhaustiveSwap2LocalImprovement.ImproveFast(perm, qap.Weights, qap.Distances, fit, new IntValue(0), new IntValue(0), qap.Maximization.Value, int.MaxValue, CancellationToken.None);
+      }
       var permutations = new List<Permutation> { perm };
       while (permutations.Count < pathCount + 1) {
         perm = (Permutation)permutations.Last().Clone();
         BiasedShuffle(perm, random);
-        permutations.Add(perm);
+        if (LocalOptima) {
+          var fit = new DoubleValue(QAPEvaluator.Apply(perm, qap.Weights, qap.Distances));
+          QAPExhaustiveSwap2LocalImprovement.ImproveFast(perm, qap.Weights, qap.Distances, fit, new IntValue(0), new IntValue(0), qap.Maximization.Value, int.MaxValue, CancellationToken.None);
+        }
+        if (HammingSimilarityCalculator.CalculateSimilarity(permutations.Last(), perm) < 0.75)
+          permutations.Add(perm);
       }
 
@@ -151 +171 @@
 
       for (var p = 0; p < f2.Count; p++) {
+        if (f2[p].Count <= 2) continue;
         var bump = 0;
         var flat = 0;
@@ -266 +287 @@
     }
 
+    // Center-of-Mass
     private static double ComBelowZero(IEnumerable<Tuple<Permutation, double>> path) {
       var area = 0.0;