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source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/BoothEvaluator.cs @ 3702

Last change on this file since 3702 was 3376, checked in by swagner, 14 years ago

Moved interfaces and classes for deep cloning from HeuristicLab.Core to HeuristicLab.Common (#975).

File size: 3.5 KB
Line 
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 Booth function is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page816.htm, last accessed April 12th, 2010.
32  /// </summary>
33  [Item("BoothEvaluator", "Evaluates the Booth function on a given point. The optimum of this function is 0 at (1,3). It is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page816.htm, last accessed April 12th, 2010.")]
34  [StorableClass]
35  public class BoothEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
36    /// <summary>
37    /// Returns false as the Booth 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[,] { { -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 maximum problem size (2).
62    /// </summary>
63    public override int MaximumProblemSize {
64      get { return 2; }
65    }
66
67    /// <summary>
68    /// Evaluates the test function for a specific <paramref name="point"/>.
69    /// </summary>
70    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
71    /// <returns>The result value of the Booth function at the given point.</returns>
72    public static double Apply(RealVector point) {
73      return (point[0] + 2 * point[1] - 7) * (point[0] + 2 * point[1] - 7)
74        + (2 * point[0] + point[1] - 5) * (2 * point[0] + point[1] - 5);
75    }
76
77    /// <summary>
78    /// Evaluates the test function for a specific <paramref name="point"/>.
79    /// </summary>
80    /// <remarks>Calls <see cref="Apply"/>.</remarks>
81    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
82    /// <returns>The result value of the Booth function at the given point.</returns>
83    protected override double EvaluateFunction(RealVector point) {
84      return Apply(point);
85    }
86  }
87}
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