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source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/LevyEvaluator.cs @ 8010

Last change on this file since 8010 was 7259, checked in by swagner, 13 years ago

Updated year of copyrights to 2012 (#1716)

File size: 4.7 KB
RevLine 
[3150]1#region License Information
2/* HeuristicLab
[7259]3 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[3150]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;
[4722]23using HeuristicLab.Common;
[3154]24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.RealVectorEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[3150]28
[3170]29namespace HeuristicLab.Problems.TestFunctions {
[3150]30  /// <summary>
[3315]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.
[3150]32  /// </summary>
[3315]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.")]
[3154]34  [StorableClass]
[3170]35  public class LevyEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
[3154]36    /// <summary>
37    /// Returns false as the Levy function is a minimization problem.
38    /// </summary>
39    public override bool Maximization {
40      get { return false; }
[3150]41    }
[3154]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[,] { { -10, 10 } }); }
53    }
54    /// <summary>
55    /// Gets the minimum problem size (2).
56    /// </summary>
57    public override int MinimumProblemSize {
58      get { return 2; }
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    }
[3150]66
[4722]67    [StorableConstructor]
68    protected LevyEvaluator(bool deserializing) : base(deserializing) { }
69    protected LevyEvaluator(LevyEvaluator original, Cloner cloner) : base(original, cloner) { }
70    public LevyEvaluator() : base() { }
71
72    public override IDeepCloneable Clone(Cloner cloner) {
73      return new LevyEvaluator(this, cloner);
74    }
75
[3781]76    public override RealVector GetBestKnownSolution(int dimension) {
77      if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension.");
78      RealVector result = new RealVector(dimension);
79      for (int i = 0; i < dimension; i++) result[i] = 1;
80      return result;
81    }
[3150]82    /// <summary>
83    /// Evaluates the test 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 Levy function at the given point.</returns>
[3154]87    public static double Apply(RealVector point) {
[3150]88      int length = point.Length;
89      double[] z = new double[length];
90      double s;
91
92      for (int i = 0; i < length; i++) {
93        z[i] = 1 + (point[i] - 1) / 4;
94      }
95
[3315]96      s = Math.Sin(Math.PI * z[0]);
[3781]97      if (Math.Abs(s) < 1e-15) s = 0; // Math.Sin(Math.PI) == 0.00000000000000012246063538223773
[3315]98      s *= s;
[3150]99
100      for (int i = 0; i < length - 1; i++) {
[3315]101        s += (z[i] - 1) * (z[i] - 1) * (1 + 10 * Math.Pow(Math.Sin(Math.PI * z[i] + 1), 2));
[3150]102      }
103
104      return s + Math.Pow(z[length - 1] - 1, 2) * (1 + Math.Pow(Math.Sin(2 * Math.PI * z[length - 1]), 2));
105    }
106
107    /// <summary>
108    /// Evaluates the test function for a specific <paramref name="point"/>.
109    /// </summary>
110    /// <remarks>Calls <see cref="Apply"/>.</remarks>
111    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
112    /// <returns>The result value of the Levy function at the given point.</returns>
[3154]113    protected override double EvaluateFunction(RealVector point) {
[3150]114      return Apply(point);
115    }
116  }
117}
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