Changeset 14666 for branches/PerformanceComparison/HeuristicLab.Algorithms.MemPR/3.3/Permutation

Timestamp:

02/11/17 01:06:37 (8 years ago)

Author:

abeham

Message:

#2457: copied MemPR algorithm from its branch to this branch

Location:

branches/PerformanceComparison/HeuristicLab.Algorithms.MemPR

Files:

• . (copied) (copied from branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR)
• 3.3/Permutation/SolutionModel/Univariate/UnivariateAbsoluteModel.cs (modified) (1 diff)
• 3.3/Permutation/SolutionModel/Univariate/UnivariateRelativeModel.cs (modified) (2 diffs)

branches/PerformanceComparison/HeuristicLab.Algorithms.MemPR/3.3/Permutation/SolutionModel/Univariate/UnivariateAbsoluteModel.cs

@@ -121 +121 @@
 
     public static UnivariateAbsoluteModel CreateWithFitnessBias(IRandom random, bool maximization, IList<Encodings.PermutationEncoding.Permutation> population, IEnumerable<double> qualities, int N) {
-      var proportions = RandomEnumerable.PrepareProportional(qualities, true, !maximization);
+      var proportions = Util.Auxiliary.PrepareProportional(qualities, true, !maximization);
       var factor = 1.0 / proportions.Sum();
       var model = new double[N, N];

branches/PerformanceComparison/HeuristicLab.Algorithms.MemPR/3.3/Permutation/SolutionModel/Univariate/UnivariateRelativeModel.cs

@@ -126 +126 @@
 
     public static UnivariateRelativeModel CreateDirectedWithFitnessBias(IRandom random, bool maximization, IList<Encodings.PermutationEncoding.Permutation> population, IEnumerable<double> qualities, int N) {
-      var proportions = RandomEnumerable.PrepareProportional(qualities, true, !maximization);
+      var proportions = Util.Auxiliary.PrepareProportional(qualities, true, !maximization);
       var factor = 1.0 / proportions.Sum();
       var model = new double[N, N];
@@ -180 +180 @@
 
     public static UnivariateRelativeModel CreateUndirectedWithFitnessBias(IRandom random, bool maximization, IList<Encodings.PermutationEncoding.Permutation> population, IEnumerable<double> qualities, int N) {
-      var proportions = RandomEnumerable.PrepareProportional(qualities, true, !maximization);
+      var proportions = Util.Auxiliary.PrepareProportional(qualities, true, !maximization);
       var factor = 1.0 / proportions.Sum();
       var model = new double[N, N];