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source: branches/OaaS/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/RastriginEvaluator.cs @ 8228

Last change on this file since 8228 was 7259, checked in by swagner, 13 years ago

Updated year of copyrights to 2012 (#1716)

File size: 5.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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 HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.RealVectorEncoding;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.TestFunctions {
31  /// <summary>
32  /// The generalized Rastrigin function y = Sum((x_i)^2 + A * (1 - Cos(2pi*x_i))) is a highly multimodal function that has its optimal value 0 at the origin.
33  /// It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.
34  /// </summary
35  [Item("RastriginEvaluator", "Evaluates the generalized Rastrigin function y = Sum((x_i)^2 + A * (1 - Cos(2pi*x_i))) on a given point. The optimum of this function is 0 at the origin. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.")]
36  [StorableClass]
37  public class RastriginEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
38    /// <summary>
39    /// Returns false as the Rastrigin function is a minimization problem.
40    /// </summary>
41    public override bool Maximization {
42      get { return false; }
43    }
44    /// <summary>
45    /// Gets the optimum function value (0).
46    /// </summary>
47    public override double BestKnownQuality {
48      get { return 0; }
49    }
50    /// <summary>
51    /// Gets the lower and upper bound of the function.
52    /// </summary>
53    public override DoubleMatrix Bounds {
54      get { return new DoubleMatrix(new double[,] { { -5.12, 5.12 } }); }
55    }
56    /// <summary>
57    /// Gets the minimum problem size (1).
58    /// </summary>
59    public override int MinimumProblemSize {
60      get { return 1; }
61    }
62    /// <summary>
63    /// Gets the (theoretical) maximum problem size (2^31 - 1).
64    /// </summary>
65    public override int MaximumProblemSize {
66      get { return int.MaxValue; }
67    }
68    /// <summary>
69    /// The parameter A is a parameter of the objective function y = Sum((x_i)^2 + A * (1 - Cos(2pi*x_i))). Default is A = 10.
70    /// </summary>
71    public ValueParameter<DoubleValue> AParameter {
72      get { return (ValueParameter<DoubleValue>)Parameters["A"]; }
73    }
74    /// <summary>
75    /// The parameter A is a parameter of the objective function y = Sum((x_i)^2 + A * (1 - Cos(2pi*x_i))). Default is A = 10.
76    /// </summary>
77    public DoubleValue A {
78      get { return AParameter.Value; }
79      set { if (value != null) AParameter.Value = value; }
80    }
81
82    public override RealVector GetBestKnownSolution(int dimension) {
83      return new RealVector(dimension);
84    }
85
86    [StorableConstructor]
87    protected RastriginEvaluator(bool deserializing) : base(deserializing) { }
88    protected RastriginEvaluator(RastriginEvaluator original, Cloner cloner) : base(original, cloner) { }
89    /// <summary>
90    /// Initializes a new instance of the RastriginEvaluator with one parameter (<c>A</c>).
91    /// </summary>
92    public RastriginEvaluator()
93      : base() {
94      Parameters.Add(new ValueParameter<DoubleValue>("A", "The parameter A is a parameter of the objective function y = Sum((x_i)^2 + A * (1 - Cos(2pi*x_i))). Default is A = 10.", new DoubleValue(10)));
95    }
96
97    public override IDeepCloneable Clone(Cloner cloner) {
98      return new RastriginEvaluator(this, cloner);
99    }
100
101    /// <summary>
102    /// Evaluates the test function for a specific <paramref name="point"/>.
103    /// </summary>
104    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
105    /// <returns>The result value of the Rastrigin function at the given point.</returns>
106    public static double Apply(RealVector point, double a) {
107      double result = a * point.Length;
108      for (int i = 0; i < point.Length; i++) {
109        result += point[i] * point[i];
110        result -= a * Math.Cos(2 * Math.PI * point[i]);
111      }
112      return (result);
113    }
114
115    /// <summary>
116    /// Evaluates the test function for a specific <paramref name="point"/>.
117    /// </summary>
118    /// <remarks>Calls <see cref="Apply"/>.</remarks>
119    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
120    /// <returns>The result value of the Rastrigin function at the given point.</returns>
121    protected override double EvaluateFunction(RealVector point) {
122      return Apply(point, A.Value);
123    }
124  }
125}
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