source: branches/ProblemRefactoring/HeuristicLab.Problems.TestFunctions/3.3/Functions/Rosenbrock.cs @ 13403

Last change on this file since 13403 was 13403, checked in by abeham, 4 years ago

#2521:

  • Adapted single-objective test function problem to new problem infrastructure
  • Added additional interfaces to RealVectorEncoding
  • Fixed IParticleUpdater interface (must implement IStochasticOperator if it contains a Random parameter)
File size: 4.8 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("Rosenbrock", @"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 Rosenbrock : SingleObjectiveTestFunction {
40    /// <summary>
41    /// Returns false as the Rosenbrock function is a minimization problem.
42    /// </summary>
43    public override bool Maximization {
44      get { return false; }
45    }
46    /// <summary>
47    /// Gets the optimum function value (0).
48    /// </summary>
49    public override double BestKnownQuality {
50      get { return 0; }
51    }
52    /// <summary>
53    /// Gets the lower and upper bound of the function.
54    /// </summary>
55    public override DoubleMatrix Bounds {
56      get { return new DoubleMatrix(new double[,] { { -2.048, 2.048 } }); }
57    }
58    /// <summary>
59    /// Gets the minimum problem size (2).
60    /// </summary>
61    public override int MinimumProblemSize {
62      get { return 2; }
63    }
64    /// <summary>
65    /// Gets the (theoretical) maximum problem size (2^31 - 1).
66    /// </summary>
67    public override int MaximumProblemSize {
68      get { return int.MaxValue; }
69    }
70
71    [StorableConstructor]
72    protected Rosenbrock(bool deserializing) : base(deserializing) { }
73    protected Rosenbrock(Rosenbrock original, Cloner cloner) : base(original, cloner) { }
74    public Rosenbrock() : base() { }
75
76    public override IDeepCloneable Clone(Cloner cloner) {
77      return new Rosenbrock(this, cloner);
78    }
79
80    public override RealVector GetBestKnownSolution(int dimension) {
81      if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension.");
82      RealVector result = new RealVector(dimension);
83      for (int i = 0; i < dimension; i++) result[i] = 1;
84      return result;
85    }
86
87    /// <summary>
88    /// Evaluates the test function for a specific <paramref name="point"/>.
89    /// </summary>
90    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
91    /// <returns>The result value of the Rosenbrock function at the given point.</returns>
92    public static double Apply(RealVector point) {
93      double result = 0;
94      for (int i = 0; i < point.Length - 1; i++) {
95        result += 100 * (point[i] * point[i] - point[i + 1]) * (point[i] * point[i] - point[i + 1]);
96        result += (point[i] - 1) * (point[i] - 1);
97      }
98      return result;
99    }
100
101    /// <summary>
102    /// Evaluates the test function for a specific <paramref name="point"/>.
103    /// </summary>
104    /// <remarks>Calls <see cref="Apply"/>.</remarks>
105    /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
106    /// <returns>The result value of the Rosenbrock function at the given point.</returns>
107    public override double Evaluate(RealVector point) {
108      return Apply(point);
109    }
110  }
111}
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