Changeset 14453 for branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/MemPRAlgorithm.cs

Timestamp:

12/05/16 12:27:19 (8 years ago)

Author:

abeham

Message:

#2701:

• Worked on MemPR algorithm for permutations
  • Made Evaluate() method mostly thread-safe and moved evaluated solutions counting to caller
• Removed TSP specific similarity calculator (it is actually not specific to the TSP) and added it to the permutation encoding as HammingSimilarityCalculator
• Fixed bug in qap basicproblem

File:

• branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/MemPRAlgorithm.cs (modified) (12 diffs)

branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/MemPRAlgorithm.cs

@@ -252 +252 @@
       var p1 = Context.AtPopulation(i1);
       var p2 = Context.AtPopulation(i2);
-
-      if (double.IsNaN(p1.Fitness)) Evaluate(p1, token);
-      if (double.IsNaN(p2.Fitness)) Evaluate(p2, token);
 
       var parentDist = Dist(p1, p2);
@@ -361 +358 @@
 
     protected int Replace(ISingleObjectiveSolutionScope<TSolution> child, CancellationToken token) {
-      if (double.IsNaN(child.Fitness)) Evaluate(child, token);
+      if (double.IsNaN(child.Fitness)) {
+        Evaluate(child, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
+      if (IsBetter(child.Fitness, Context.BestQuality)) {
+        Context.BestQuality = child.Fitness;
+        Context.BestSolution = (TSolution)child.Solution.Clone();
+      }
 
       var popSize = MaximumPopulationSize;
@@ -460 +464 @@
     protected abstract ISolutionSubspace<TSolution> CalculateSubspace(IEnumerable<TSolution> solutions, bool inverse = false);
     protected virtual void Evaluate(ISingleObjectiveSolutionScope<TSolution> scope, CancellationToken token) {
-      Context.EvaluatedSolutions++;
       var prob = Problem as ISingleObjectiveProblemDefinition;
       if (prob != null) {
@@ -466 +469 @@
         scope.Fitness = prob.Evaluate(ind, Context.Random);
       } else RunOperator(Problem.Evaluator, scope, token);
-      if (IsBetter(scope.Fitness, Context.BestQuality))
-        Context.BestQuality = scope.Fitness;
     }
 
@@ -480 +481 @@
     #region Improve
     protected virtual int HillClimb(ISingleObjectiveSolutionScope<TSolution> scope, CancellationToken token, ISolutionSubspace<TSolution> subspace = null) {
-      if (double.IsNaN(scope.Fitness)) Evaluate(scope, token);
+      if (double.IsNaN(scope.Fitness)) {
+        Evaluate(scope, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
       var before = scope.Fitness;
       var lscontext = Context.CreateSingleSolutionContext(scope);
@@ -486 +490 @@
       var after = scope.Fitness;
       Context.HillclimbingStat.Add(Tuple.Create(before, after));
+      Context.IncrementEvaluatedSolutions(lscontext.EvaluatedSolutions);
       return lscontext.Iterations;
     }
 
     protected virtual void PerformTabuWalk(ISingleObjectiveSolutionScope<TSolution> scope, int steps, CancellationToken token, ISolutionSubspace<TSolution> subspace = null) {
-      if (double.IsNaN(scope.Fitness)) Evaluate(scope, token);
+      if (double.IsNaN(scope.Fitness)) {
+        Evaluate(scope, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
       var before = scope.Fitness;
       var newScope = (ISingleObjectiveSolutionScope<TSolution>)scope.Clone();
@@ -500 +508 @@
     protected abstract void TabuWalk(ISingleObjectiveSolutionScope<TSolution> scope, int steps, CancellationToken token, ISolutionSubspace<TSolution> subspace = null);
     protected virtual void TabuClimb(ISingleObjectiveSolutionScope<TSolution> scope, int steps, CancellationToken token, ISolutionSubspace<TSolution> subspace = null) {
-      if (double.IsNaN(scope.Fitness)) Evaluate(scope, token);
+      if (double.IsNaN(scope.Fitness)) {
+        Evaluate(scope, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
       var before = scope.Fitness;
       var newScope = (ISingleObjectiveSolutionScope<TSolution>)scope.Clone();
@@ -520 +531 @@
       var p2 = Context.AtPopulation(i2);
 
-      if (double.IsNaN(p1.Fitness)) Evaluate(p1, token);
-      if (double.IsNaN(p2.Fitness)) Evaluate(p2, token);
+      if (double.IsNaN(p1.Fitness)) {
+        Evaluate(p1, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
+      if (double.IsNaN(p2.Fitness)) {
+        Evaluate(p2, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
 
       return BreedAndImprove(p1, p2, token);
@@ -532 +549 @@
         Mutate(offspring, token, subspace); // mutate the solutions, especially to widen the sub-space
       }
-      if (double.IsNaN(offspring.Fitness)) Evaluate(offspring, token);
+      if (double.IsNaN(offspring.Fitness)) {
+        Evaluate(offspring, token);
+        Context.IncrementEvaluatedSolutions(1);
+      }
       Context.BreedingStat.Add(Tuple.Create(p1.Fitness, p2.Fitness, offspring.Fitness));
       if ((IsBetter(offspring, p1) && IsBetter(offspring, p2))
@@ -556 +576 @@
       var p2 = Context.AtPopulation(i2);
 
-      if (double.IsNaN(p1.Fitness)) Evaluate(p1, token);
-      if (double.IsNaN(p2.Fitness)) Evaluate(p2, token);
-
       return RelinkAndImprove(p1, p2, token);
     }
@@ -584 +601 @@
       SolutionModelTrainerParameter.Value.TrainModel(Context);
       var sample = ToScope(Context.Model.Sample());
+      Evaluate(sample, token);
+      Context.IncrementEvaluatedSolutions(1);
       if (Context.Population.Any(p => IsBetter(sample, p) || sample.Fitness == p.Fitness)) return sample;
 
@@ -608 +627 @@
 
     protected double ProbabilityAccept(ISingleObjectiveSolutionScope<TSolution> scope, IList<Tuple<double, double>> data) {
-      if (double.IsNaN(scope.Fitness)) Evaluate(scope, CancellationToken.None);
+      if (double.IsNaN(scope.Fitness)) {
+        Evaluate(scope, CancellationToken.None);
+        Context.IncrementEvaluatedSolutions(1);
+      }
       return ProbabilityAccept(scope.Fitness, data);
     }