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source: branches/Operator Architecture Refactoring/HeuristicLab.RealVector/SelfAdaptiveNormalAllPositionsManipulator.cs @ 771

Last change on this file since 771 was 99, checked in by abeham, 17 years ago

Added sigma self adaptive operators for RealVector problems

File size: 2.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Text;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Random;
28
29namespace HeuristicLab.RealVector {
30  public class SelfAdaptiveNormalAllPositionsManipulator : RealVectorManipulatorBase {
31    public override string Description {
32      get { return @"Manipulates each dimension in the real vector with the mutation strength given in the strategy parameter vector"; }
33    }
34
35    public SelfAdaptiveNormalAllPositionsManipulator()
36      : base() {
37      AddVariableInfo(new VariableInfo("StrategyVector", "The strategy vector determining the strength of the mutation", typeof(DoubleArrayData), VariableKind.In));
38    }
39
40    public static double[] Apply(double[] strategyParameters, IRandom random, double[] vector) {
41      NormalDistributedRandom N = new NormalDistributedRandom(random, 0.0, 1.0);
42      if (strategyParameters.Length != vector.Length)
43        throw new InvalidOperationException("ERROR: Strategy Vector must be as long as parameter vector");
44      for (int i = 0; i < vector.Length; i++) {
45        vector[i] = vector[i] + (N.NextDouble() * strategyParameters[i]);
46      }
47      return vector;
48    }
49
50    protected override double[] Manipulate(IScope scope, IRandom random, double[] vector) {
51      double[] strategyVector = scope.GetVariableValue<DoubleArrayData>("StrategyVector", true).Data;
52      return Apply(strategyVector, random, vector);
53    }
54  }
55}
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