source: branches/ProblemRefactoring/HeuristicLab.Problems.TestFunctions/3.3/Functions/Schwefel.cs @ 13403

Last change on this file since 13403 was 13403, checked in by abeham, 4 years ago

#2521:

  • Adapted single-objective test function problem to new problem infrastructure
  • Added additional interfaces to RealVectorEncoding
  • Fixed IParticleUpdater interface (must implement IStochasticOperator if it contains a Random parameter)
File size: 4.4 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("Schwefel", "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 Schwefel : SingleObjectiveTestFunction {
36    /// <summary>
37    /// Returns false as the Schwefel (sine root) function is a minimization problem.
38    /// </summary>
39    public override bool Maximization {
40      get { return false; }
41    }
42    /// <summary>
43    /// Gets the optimum function value (0).
44    /// </summary>
45    public override double BestKnownQuality {
46      get { return 0; }
47    }
48    /// <summary>
49    /// Gets the lower and upper bound of the function.
50    /// </summary>
51    public override DoubleMatrix Bounds {
52      get { return new DoubleMatrix(new double[,] { { -500, 500 } }); }
53    }
54    /// <summary>
55    /// Gets the minimum problem size (1).
56    /// </summary>
57    public override int MinimumProblemSize {
58      get { return 1; }
59    }
60    /// <summary>
61    /// Gets the (theoretical) maximum problem size (2^31 - 1).
62    /// </summary>
63    public override int MaximumProblemSize {
64      get { return int.MaxValue; }
65    }
66
67    [StorableConstructor]
68    protected Schwefel(bool deserializing) : base(deserializing) { }
69    protected Schwefel(Schwefel original, Cloner cloner) : base(original, cloner) { }
70    public Schwefel() : base() { }
71
72    public override IDeepCloneable Clone(Cloner cloner) {
73      return new Schwefel(this, cloner);
74    }
75
76    public override RealVector GetBestKnownSolution(int dimension) {
77      return null;
78    }
79
80    /// <summary>
81    /// Evaluates the test function for a specific <paramref name="point"/>.
82    /// </summary>
83    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
84    /// <returns>The result value of the Schwefel function at the given point.</returns>
85    public static double Apply(RealVector point) {
86      double result = 418.982887272433 * point.Length;
87      for (int i = 0; i < point.Length; i++)
88        result -= point[i] * Math.Sin(Math.Sqrt(Math.Abs(point[i])));
89      return (result);
90    }
91
92    /// <summary>
93    /// Evaluates the test function for a specific <paramref name="point"/>.
94    /// </summary>
95    /// <remarks>Calls <see cref="Apply"/>.</remarks>
96    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
97    /// <returns>The result value of the Schwefel function at the given point.</returns>
98    public override double Evaluate(RealVector point) {
99      return Apply(point);
100    }
101  }
102}
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