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source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/RosenbrockEvaluator.cs @ 3318

Last change on this file since 3318 was 3318, checked in by abeham, 14 years ago

Updated test functions, added reference for Zakharov
Did not find a reference for SumSquares, just described it
Added wiring for rastrigin and sphere
#934

File size: 4.1 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.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Encodings.RealVectorEncoding;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Problems.TestFunctions {
29  /// <summary>
30  /// The Rosenbrock function features a flat valley in which the global optimum is located.
31  /// It is implemented as generalized Rosenbrock function as for example given in Shang, Y.-W. and Qiu, Y.-H. 2006. A Note on the Extended Rosenbrock Function. Evolutionary Computation 14, pp. 119-126, MIT Press.
32  /// </summary>
33  [Item("RosenbrockEvaluator", @"The Rosenbrock function features a flat valley in which the global optimum is located.
34For 2 and 3 dimensions the single minimum of this function is 0 at (1,1,...,1), for 4 to 30 dimensions there is an additional local minimum close to (-1,1,...,1).
35It is unknown how many local minima there are for dimensions greater than 30.
36It is implemented as generalized Rosenbrock function for which the 2 dimensional function is a special case, as for example given in Shang, Y.-W. and Qiu, Y.-H. 2006. A Note on the Extended Rosenbrock Function. Evolutionary Computation 14, pp. 119-126, MIT Press.")]
37  [StorableClass]
38  public class RosenbrockEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
39    /// <summary>
40    /// Returns false as the Rosenbrock function is a minimization problem.
41    /// </summary>
42    public override bool Maximization {
43      get { return false; }
44    }
45    /// <summary>
46    /// Gets the optimum function value (0).
47    /// </summary>
48    public override double BestKnownQuality {
49      get { return 0; }
50    }
51    /// <summary>
52    /// Gets the lower and upper bound of the function.
53    /// </summary>
54    public override DoubleMatrix Bounds {
55      get { return new DoubleMatrix(new double[,] { { -2.048, 2.048 } }); }
56    }
57    /// <summary>
58    /// Gets the minimum problem size (2).
59    /// </summary>
60    public override int MinimumProblemSize {
61      get { return 2; }
62    }
63    /// <summary>
64    /// Gets the (theoretical) maximum problem size (2^31 - 1).
65    /// </summary>
66    public override int MaximumProblemSize {
67      get { return int.MaxValue; }
68    }
69
70    /// <summary>
71    /// Evaluates the test function for a specific <paramref name="point"/>.
72    /// </summary>
73    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
74    /// <returns>The result value of the Rosenbrock function at the given point.</returns>
75    public static double Apply(RealVector point) {
76      double result = 0;
77      for (int i = 0; i < point.Length - 1; i++) {
78        result += 100 * (point[i] * point[i] - point[i + 1]) * (point[i] * point[i] - point[i + 1]);
79        result += (point[i] - 1) * (point[i] - 1);
80      }
81      return result;
82    }
83
84    /// <summary>
85    /// Evaluates the test function for a specific <paramref name="point"/>.
86    /// </summary>
87    /// <remarks>Calls <see cref="Apply"/>.</remarks>
88    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
89    /// <returns>The result value of the Rosenbrock function at the given point.</returns>
90    protected override double EvaluateFunction(RealVector point) {
91      return Apply(point);
92    }
93  }
94}
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