source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/SchwefelEvaluator.cs @ 12012

Last change on this file since 12012 was 12012, checked in by ascheibe, 5 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 4.6 KB
Line 
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.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.TestFunctions {
30  /// <summary>
31  /// The Schwefel function (sine root) is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms.  Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218-221, Springer.
32  /// </summary>
33  [Item("SchwefelEvaluator", "Evaluates the Schwefel function (sine root) on a given point. In the given bounds [-500;500] the optimum of this function is close to 0 at (420.968746453712,420.968746453712,...,420.968746453712). It is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms.  Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218-221, Springer.")]
34  [StorableClass]
35  public class SchwefelEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
36    public override string FunctionName { get { return "Schwefel"; } }
37    /// <summary>
38    /// Returns false as the Schwefel (sine root) 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[,] { { -500, 500 } }); }
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 SchwefelEvaluator(bool deserializing) : base(deserializing) { }
70    protected SchwefelEvaluator(SchwefelEvaluator original, Cloner cloner) : base(original, cloner) { }
71    public SchwefelEvaluator() : base() { }
72
73    public override IDeepCloneable Clone(Cloner cloner) {
74      return new SchwefelEvaluator(this, cloner);
75    }
76
77    public override RealVector GetBestKnownSolution(int dimension) {
78      return null;
79    }
80
81    /// <summary>
82    /// Evaluates the test 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 Schwefel function at the given point.</returns>
86    public static double Apply(RealVector point) {
87      double result = 418.982887272433 * point.Length;
88      for (int i = 0; i < point.Length; i++)
89        result -= point[i] * Math.Sin(Math.Sqrt(Math.Abs(point[i])));
90      return (result);
91    }
92
93    /// <summary>
94    /// Evaluates the test function for a specific <paramref name="point"/>.
95    /// </summary>
96    /// <remarks>Calls <see cref="Apply"/>.</remarks>
97    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
98    /// <returns>The result value of the Schwefel function at the given point.</returns>
99    public override double Evaluate(RealVector point) {
100      return Apply(point);
101    }
102  }
103}
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