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source: stable/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/RastriginEvaluator.cs @ 13957

Last change on this file since 13957 was 12009, checked in by ascheibe, 10 years ago

#2212 updated copyright year

File size: 5.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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    public override string FunctionName { get { return "Rastrigin"; } }
39    /// <summary>
40    /// Returns false as the Rastrigin function is a minimization problem.
41    /// </summary>
42    public override bool Maximization {
43      get { return false; }
44    }
45    /// <summary>
46    /// Gets the optimum function value (0).
47    /// </summary>
48    public override double BestKnownQuality {
49      get { return 0; }
50    }
51    /// <summary>
52    /// Gets the lower and upper bound of the function.
53    /// </summary>
54    public override DoubleMatrix Bounds {
55      get { return new DoubleMatrix(new double[,] { { -5.12, 5.12 } }); }
56    }
57    /// <summary>
58    /// Gets the minimum problem size (1).
59    /// </summary>
60    public override int MinimumProblemSize {
61      get { return 1; }
62    }
63    /// <summary>
64    /// Gets the (theoretical) maximum problem size (2^31 - 1).
65    /// </summary>
66    public override int MaximumProblemSize {
67      get { return int.MaxValue; }
68    }
69    /// <summary>
70    /// 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.
71    /// </summary>
72    public ValueParameter<DoubleValue> AParameter {
73      get { return (ValueParameter<DoubleValue>)Parameters["A"]; }
74    }
75    /// <summary>
76    /// 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.
77    /// </summary>
78    public DoubleValue A {
79      get { return AParameter.Value; }
80      set { if (value != null) AParameter.Value = value; }
81    }
82
83    public override RealVector GetBestKnownSolution(int dimension) {
84      return new RealVector(dimension);
85    }
86
87    [StorableConstructor]
88    protected RastriginEvaluator(bool deserializing) : base(deserializing) { }
89    protected RastriginEvaluator(RastriginEvaluator original, Cloner cloner) : base(original, cloner) { }
90    /// <summary>
91    /// Initializes a new instance of the RastriginEvaluator with one parameter (<c>A</c>).
92    /// </summary>
93    public RastriginEvaluator()
94      : base() {
95      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)));
96    }
97
98    public override IDeepCloneable Clone(Cloner cloner) {
99      return new RastriginEvaluator(this, cloner);
100    }
101
102    /// <summary>
103    /// Evaluates the test function for a specific <paramref name="point"/>.
104    /// </summary>
105    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
106    /// <returns>The result value of the Rastrigin function at the given point.</returns>
107    public static double Apply(RealVector point, double a) {
108      double result = a * point.Length;
109      for (int i = 0; i < point.Length; i++) {
110        result += point[i] * point[i];
111        result -= a * Math.Cos(2 * Math.PI * point[i]);
112      }
113      return (result);
114    }
115
116    /// <summary>
117    /// Evaluates the test function for a specific <paramref name="point"/>.
118    /// </summary>
119    /// <remarks>Calls <see cref="Apply"/>.</remarks>
120    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
121    /// <returns>The result value of the Rastrigin function at the given point.</returns>
122    public override double Evaluate(RealVector point) {
123      return Apply(point, A.Value);
124    }
125  }
126}
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