source: trunk/sources/HeuristicLab.Problems.TestFunctions/3.3/Evaluators/RosenbrockEvaluator.cs @ 12012

Last change on this file since 12012 was 12012, checked in by ascheibe, 5 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 4.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 Rosenbrock function features a flat valley in which the global optimum is located.
32  /// 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.
33  /// </summary>
34  [Item("RosenbrockEvaluator", @"The Rosenbrock function features a flat valley in which the global optimum is located.
35For 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).
36It is unknown how many local minima there are for dimensions greater than 30.
37It 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.")]
38  [StorableClass]
39  public class RosenbrockEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
40    public override string FunctionName { get { return "Rosenbrock"; } }
41    /// <summary>
42    /// Returns false as the Rosenbrock function is a minimization problem.
43    /// </summary>
44    public override bool Maximization {
45      get { return false; }
46    }
47    /// <summary>
48    /// Gets the optimum function value (0).
49    /// </summary>
50    public override double BestKnownQuality {
51      get { return 0; }
52    }
53    /// <summary>
54    /// Gets the lower and upper bound of the function.
55    /// </summary>
56    public override DoubleMatrix Bounds {
57      get { return new DoubleMatrix(new double[,] { { -2.048, 2.048 } }); }
58    }
59    /// <summary>
60    /// Gets the minimum problem size (2).
61    /// </summary>
62    public override int MinimumProblemSize {
63      get { return 2; }
64    }
65    /// <summary>
66    /// Gets the (theoretical) maximum problem size (2^31 - 1).
67    /// </summary>
68    public override int MaximumProblemSize {
69      get { return int.MaxValue; }
70    }
71
72    [StorableConstructor]
73    protected RosenbrockEvaluator(bool deserializing) : base(deserializing) { }
74    protected RosenbrockEvaluator(RosenbrockEvaluator original, Cloner cloner) : base(original, cloner) { }
75    public RosenbrockEvaluator() : base() { }
76
77    public override IDeepCloneable Clone(Cloner cloner) {
78      return new RosenbrockEvaluator(this, cloner);
79    }
80
81    public override RealVector GetBestKnownSolution(int dimension) {
82      if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension.");
83      RealVector result = new RealVector(dimension);
84      for (int i = 0; i < dimension; i++) result[i] = 1;
85      return result;
86    }
87
88    /// <summary>
89    /// Evaluates the test function for a specific <paramref name="point"/>.
90    /// </summary>
91    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
92    /// <returns>The result value of the Rosenbrock function at the given point.</returns>
93    public static double Apply(RealVector point) {
94      double result = 0;
95      for (int i = 0; i < point.Length - 1; i++) {
96        result += 100 * (point[i] * point[i] - point[i + 1]) * (point[i] * point[i] - point[i + 1]);
97        result += (point[i] - 1) * (point[i] - 1);
98      }
99      return result;
100    }
101
102    /// <summary>
103    /// Evaluates the test function for a specific <paramref name="point"/>.
104    /// </summary>
105    /// <remarks>Calls <see cref="Apply"/>.</remarks>
106    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
107    /// <returns>The result value of the Rosenbrock function at the given point.</returns>
108    public override double Evaluate(RealVector point) {
109      return Apply(point);
110    }
111  }
112}
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