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source: stable/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/BealeEvaluator.cs @ 17234

Last change on this file since 17234 was 17181, checked in by swagner, 5 years ago

#2875: Merged r17180 from trunk to stable

File size: 4.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 HEAL.Attic;
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  [StorableType("EC1E155C-65ED-4603-A442-357ECC1E8F3D")]
36  public class BealeEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
37    public override string FunctionName { get { return "Beale"; } }
38    /// <summary>
39    /// Returns false as the Beale function is a minimization problem.
40    /// </summary>
41    public override bool Maximization {
42      get { return false; }
43    }
44    /// <summary>
45    /// Gets the optimum function value (0).
46    /// </summary>
47    public override double BestKnownQuality {
48      get { return 0; }
49    }
50    /// <summary>
51    /// Gets the lower and upper bound of the function.
52    /// </summary>
53    public override DoubleMatrix Bounds {
54      get { return new DoubleMatrix(new double[,] { { -4.5, 4.5 } }); }
55    }
56    /// <summary>
57    /// Gets the minimum problem size (2).
58    /// </summary>
59    public override int MinimumProblemSize {
60      get { return 2; }
61    }
62    /// <summary>
63    /// Gets the maximum problem size (2).
64    /// </summary>
65    public override int MaximumProblemSize {
66      get { return 2; }
67    }
68
69    [StorableConstructor]
70    protected BealeEvaluator(StorableConstructorFlag _) : base(_) { }
71    protected BealeEvaluator(BealeEvaluator original, Cloner cloner) : base(original, cloner) { }
72    public BealeEvaluator() : base() { }
73
74    public override IDeepCloneable Clone(Cloner cloner) {
75      return new BealeEvaluator(this, cloner);
76    }
77
78    public override RealVector GetBestKnownSolution(int dimension) {
79      if (dimension != 2) throw new ArgumentException(Name + ": This function is only defined for 2 dimensions.", "dimension");
80      return new RealVector(new double[] { 3, 0.5 });
81    }
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 Beale function at the given point.</returns>
87    public static double Apply(RealVector point) {
88      double x1 = point[0], x2 = point[1];
89      double f1 = 1.5 - x1 * (1 - x2);
90      double f2 = 2.25 - x1 * (1 - x2 * x2);
91      double f3 = 2.625 - x1 * (1 - x2 * x2 * x2);
92      return (f1 * f1) + (f2 * f2) + (f3 * f3);
93    }
94
95    /// <summary>
96    /// Evaluates the test function for a specific <paramref name="point"/>.
97    /// </summary>
98    /// <remarks>Calls <see cref="Apply"/>.</remarks>
99    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
100    /// <returns>The result value of the Beale function at the given point.</returns>
101    public override double Evaluate(RealVector point) {
102      return Apply(point);
103    }
104  }
105}
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