source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/LevyEvaluator.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: 4.7 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 Levy function is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2056.htm, last accessed April 12th, 2010.
32  /// </summary>
33  [Item("LevyEvaluator", "Evaluates the Levy function on a given point. The optimum of this function is 0 at (1,1,...,1). It is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2056.htm, last accessed April 12th, 2010.")]
34  [StorableClass]
35  public class LevyEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
36    public override string FunctionName { get { return "Levy"; } }
37    /// <summary>
38    /// Returns false as the Levy 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[,] { { -10, 10 } }); }
54    }
55    /// <summary>
56    /// Gets the minimum problem size (2).
57    /// </summary>
58    public override int MinimumProblemSize {
59      get { return 2; }
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 LevyEvaluator(bool deserializing) : base(deserializing) { }
70    protected LevyEvaluator(LevyEvaluator original, Cloner cloner) : base(original, cloner) { }
71    public LevyEvaluator() : base() { }
72
73    public override IDeepCloneable Clone(Cloner cloner) {
74      return new LevyEvaluator(this, cloner);
75    }
76
77    public override RealVector GetBestKnownSolution(int dimension) {
78      if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension.");
79      RealVector result = new RealVector(dimension);
80      for (int i = 0; i < dimension; i++) result[i] = 1;
81      return result;
82    }
83    /// <summary>
84    /// Evaluates the test function for a specific <paramref name="point"/>.
85    /// </summary>
86    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
87    /// <returns>The result value of the Levy function at the given point.</returns>
88    public static double Apply(RealVector point) {
89      int length = point.Length;
90      double[] z = new double[length];
91      double s;
92
93      for (int i = 0; i < length; i++) {
94        z[i] = 1 + (point[i] - 1) / 4;
95      }
96
97      s = Math.Sin(Math.PI * z[0]);
98      if (Math.Abs(s) < 1e-15) s = 0; // Math.Sin(Math.PI) == 0.00000000000000012246063538223773
99      s *= s;
100
101      for (int i = 0; i < length - 1; i++) {
102        s += (z[i] - 1) * (z[i] - 1) * (1 + 10 * Math.Pow(Math.Sin(Math.PI * z[i] + 1), 2));
103      }
104
105      return s + Math.Pow(z[length - 1] - 1, 2) * (1 + Math.Pow(Math.Sin(2 * Math.PI * z[length - 1]), 2));
106    }
107
108    /// <summary>
109    /// Evaluates the test function for a specific <paramref name="point"/>.
110    /// </summary>
111    /// <remarks>Calls <see cref="Apply"/>.</remarks>
112    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
113    /// <returns>The result value of the Levy function at the given point.</returns>
114    public override double Evaluate(RealVector point) {
115      return Apply(point);
116    }
117  }
118}
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