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source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/BealeEvaluator.cs @ 5182

Last change on this file since 5182 was 4722, checked in by swagner, 14 years ago

Merged cloning refactoring branch back into trunk (#922)

File size: 4.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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 Beale function is defined for 2 dimensions with an optimum of 0 at (3, 0.5).
32  /// It is implemented as described in Moré, J.J., Garbow, B., and Hillstrom, K. 1981. Testing unconstrained optimization software. ACM Transactions on Mathematical Software 7, pp. 136-140, ACM.
33  /// </summary>
34  [Item("BealeEvaluator", "Evaluates the Beale function on a given point. The optimum of this function is 0 at (3,0.5). It is implemented as described in Moré, J.J., Garbow, B., and Hillstrom, K. 1981. Testing unconstrained optimization software. ACM Transactions on Mathematical Software 7, pp. 136-140, ACM.")]
35  [StorableClass]
36  public class BealeEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
37    /// <summary>
38    /// Returns false as the Beale 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[,] { { -4.5, 4.5 } }); }
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 maximum problem size (2).
63    /// </summary>
64    public override int MaximumProblemSize {
65      get { return 2; }
66    }
67
68    [StorableConstructor]
69    protected BealeEvaluator(bool deserializing) : base(deserializing) { }
70    protected BealeEvaluator(BealeEvaluator original, Cloner cloner) : base(original, cloner) { }
71    public BealeEvaluator() : base() { }
72
73    public override IDeepCloneable Clone(Cloner cloner) {
74      return new BealeEvaluator(this, cloner);
75    }
76
77    public override RealVector GetBestKnownSolution(int dimension) {
78      if (dimension != 2) throw new ArgumentException(Name + ": This function is only defined for 2 dimensions.", "dimension");
79      return new RealVector(new double[] { 3, 0.5 });
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 Beale function at the given point.</returns>
86    public static double Apply(RealVector point) {
87      double x1 = point[0], x2 = point[1];
88      double f1 = 1.5 - x1 * (1 - x2);
89      double f2 = 2.25 - x1 * (1 - x2 * x2);
90      double f3 = 2.625 - x1 * (1 - x2 * x2 * x2);
91      return (f1 * f1) + (f2 * f2) + (f3 * f3);
92    }
93
94    /// <summary>
95    /// Evaluates the test function for a specific <paramref name="point"/>.
96    /// </summary>
97    /// <remarks>Calls <see cref="Apply"/>.</remarks>
98    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
99    /// <returns>The result value of the Beale function at the given point.</returns>
100    protected override double EvaluateFunction(RealVector point) {
101      return Apply(point);
102    }
103  }
104}
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