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source: branches/CloningRefactoring/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/AckleyEvaluator.cs @ 4688

Last change on this file since 4688 was 4688, checked in by swagner, 13 years ago

Finished cloning refactoring of HeuristicLab.Problems.TestFunctions (#922)

File size: 4.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.TestFunctions {
30  /// <summary>
31  /// The Ackley function as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg
32  /// is highly multimodal. It has a single global minimum at the origin with value 0.
33  /// </summary
34  [Item("AckleyEvaluator", "Evaluates the Ackley function 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.")]
35  [StorableClass]
36  public class AckleyEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
37    /// <summary>
38    /// Returns false as the Ackley function is a minimization problem.
39    /// </summary>
40    public override bool Maximization {
41      get { return false; }
42    }
43    /// <summary>
44    /// Gets the optimum function value (0).
45    /// </summary>
46    public override double BestKnownQuality {
47      get { return 0; }
48    }
49    /// <summary>
50    /// Gets the lower and upper bound of the function.
51    /// </summary>
52    public override DoubleMatrix Bounds {
53      get { return new DoubleMatrix(new double[,] { { -32.768, 32.768 } }); }
54    }
55    /// <summary>
56    /// Gets the minimum problem size (1).
57    /// </summary>
58    public override int MinimumProblemSize {
59      get { return 1; }
60    }
61    /// <summary>
62    /// Gets the (theoretical) maximum problem size (2^31 - 1).
63    /// </summary>
64    public override int MaximumProblemSize {
65      get { return int.MaxValue; }
66    }
67
68    [StorableConstructor]
69    protected AckleyEvaluator(bool deserializing) : base(deserializing) { }
70    protected AckleyEvaluator(AckleyEvaluator original, Cloner cloner) : base(original, cloner) { }
71    public AckleyEvaluator() : base() { }
72
73    public override IDeepCloneable Clone(Cloner cloner) {
74      return new AckleyEvaluator(this, cloner);
75    }
76
77    public override RealVector GetBestKnownSolution(int dimension) {
78      return new RealVector(dimension);
79    }
80
81    /// <summary>
82    /// Evaluates the Ackley function for a specific <paramref name="point"/>.
83    /// </summary>
84    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
85    /// <returns>The result value of the Ackley function at the given point.</returns>
86    public static double Apply(RealVector point) {
87      double result;
88      double val;
89
90      val = 0;
91      for (int i = 0; i < point.Length; i++)
92        val += point[i] * point[i];
93      val /= point.Length;
94      val = -0.2 * Math.Sqrt(val);
95      result = 20 - 20 * Math.Exp(val);
96
97      val = 0;
98      for (int i = 0; i < point.Length; i++)
99        val += Math.Cos(2 * Math.PI * point[i]);
100      val /= point.Length;
101      result += Math.E - Math.Exp(val);
102      return (result);
103    }
104
105    /// <summary>
106    /// Evaluates the test function for a specific <paramref name="point"/>.
107    /// </summary>
108    /// <remarks>Calls <see cref="Apply"/>.</remarks>
109    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
110    /// <returns>The result value of the Ackley function at the given point.</returns>
111    protected override double EvaluateFunction(RealVector point) {
112      return Apply(point);
113    }
114  }
115}
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