Changeset 13851 for branches/ichiriac/HeuristicLab.Algorithms.DifferentialEvolution

Timestamp:

05/18/16 17:52:11 (9 years ago)

Author:

ichiriac

Message:

Add licence information

File:

• branches/ichiriac/HeuristicLab.Algorithms.DifferentialEvolution/DifferentialEvolution.cs (modified) (4 diffs)

branches/ichiriac/HeuristicLab.Algorithms.DifferentialEvolution/DifferentialEvolution.cs

@@ -1 @@
-using HeuristicLab.Analysis;
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ * Implementation is based on jMetal framework https://github.com/jMetal/jMetal
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+using HeuristicLab.Analysis;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -175 +196 @@
             Parameters.Add(new FixedValueParameter<IntValue>(SeedParameterName, "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
             Parameters.Add(new FixedValueParameter<BoolValue>(SetSeedRandomlyParameterName, "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
-            Parameters.Add(new ValueParameter<IntValue>(PopulationSizeParameterName, "The size of the population of solutions.", new IntValue(75)));
+            Parameters.Add(new ValueParameter<IntValue>(PopulationSizeParameterName, "The size of the population of solutions.", new IntValue(100)));
             Parameters.Add(new ValueParameter<DoubleValue>(CrossoverProbabilityParameterName, "The value for crossover rate", new DoubleValue(0.88)));
             Parameters.Add(new ValueParameter<DoubleValue>(ScalingFactorParameterName, "The value for scaling factor", new DoubleValue(0.47)));
-            Parameters.Add(new ValueParameter<DoubleValue>(ValueToReachParameterName, "Value to reach (VTR) parameter", new DoubleValue(0.000001)));
+            Parameters.Add(new ValueParameter<DoubleValue>(ValueToReachParameterName, "Value to reach (VTR) parameter", new DoubleValue(0.00000001)));
         }
 
@@ -201 +222 @@
             var range = ub - lb;
             this.evals = 0;
+
             double[,] populationOld = new double[PopulationSizeParameter.Value.Value, Problem.ProblemSize.Value];
             double[,] mutationPopulation = new double[PopulationSizeParameter.Value.Value, Problem.ProblemSize.Value];
@@ -252 +274 @@
             // Loop until iteration limit reached or canceled.
             // todo replace with a function
-            while (ResultsIterations < MaximumEvaluations
+            // && bestPopulationValue > Problem.BestKnownQuality.Value + ValueToReachParameter.Value.Value
+            while (ResultsEvaluations < MaximumEvaluations
                 && !cancellationToken.IsCancellationRequested
-                && bestPopulationValue > Problem.BestKnownQuality.Value + ValueToReachParameter.Value.Value)
+                && (bestPopulationValue - Problem.BestKnownQuality.Value) > ValueToReachParameter.Value.Value)
             {
-
                 //mutation DE/rand/1/bin; classic DE
                 for (int i = 0; i < PopulationSizeParameter.Value.Value; i++)