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source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/AckleyEvaluator.cs @ 11210

Last change on this file since 11210 was 11171, checked in by ascheibe, 10 years ago

#2115 merged r11170 (copyright update) into trunk

File size: 4.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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    public override string FunctionName { get { return "Ackley"; } }
38    /// <summary>
39    /// Returns false as the Ackley 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[,] { { -32.768, 32.768 } }); }
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
69    [StorableConstructor]
70    protected AckleyEvaluator(bool deserializing) : base(deserializing) { }
71    protected AckleyEvaluator(AckleyEvaluator original, Cloner cloner) : base(original, cloner) { }
72    public AckleyEvaluator() : base() { }
73
74    public override IDeepCloneable Clone(Cloner cloner) {
75      return new AckleyEvaluator(this, cloner);
76    }
77
78    public override RealVector GetBestKnownSolution(int dimension) {
79      return new RealVector(dimension);
80    }
81
82    /// <summary>
83    /// Evaluates the Ackley function for a specific <paramref name="point"/>.
84    /// </summary>
85    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
86    /// <returns>The result value of the Ackley function at the given point.</returns>
87    public static double Apply(RealVector point) {
88      double result;
89      double val;
90
91      val = 0;
92      for (int i = 0; i < point.Length; i++)
93        val += point[i] * point[i];
94      val /= point.Length;
95      val = -0.2 * Math.Sqrt(val);
96      result = 20 - 20 * Math.Exp(val);
97
98      val = 0;
99      for (int i = 0; i < point.Length; i++)
100        val += Math.Cos(2 * Math.PI * point[i]);
101      val /= point.Length;
102      result += Math.E - Math.Exp(val);
103      return (result);
104    }
105
106    /// <summary>
107    /// Evaluates the test function for a specific <paramref name="point"/>.
108    /// </summary>
109    /// <remarks>Calls <see cref="Apply"/>.</remarks>
110    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
111    /// <returns>The result value of the Ackley function at the given point.</returns>
112    public override double Evaluate(RealVector point) {
113      return Apply(point);
114    }
115  }
116}
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