1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Encodings.RealVectorEncoding;
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27 | using HEAL.Fossil;
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28 |
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29 | namespace HeuristicLab.Problems.TestFunctions {
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30 | /// <summary>
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31 | /// The Rosenbrock function features a flat valley in which the global optimum is located.
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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.
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33 | /// </summary>
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34 | [Item("RosenbrockEvaluator", @"The Rosenbrock function features a flat valley in which the global optimum is located.
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35 | For 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).
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36 | It is unknown how many local minima there are for dimensions greater than 30.
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37 | It 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.")]
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38 | [StorableType("20C31FDB-4F7D-4563-B955-F4F8B34DFF3E")]
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39 | public class RosenbrockEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
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40 | public override string FunctionName { get { return "Rosenbrock"; } }
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41 | /// <summary>
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42 | /// Returns false as the Rosenbrock function is a minimization problem.
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43 | /// </summary>
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44 | public override bool Maximization {
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45 | get { return false; }
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46 | }
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47 | /// <summary>
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48 | /// Gets the optimum function value (0).
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49 | /// </summary>
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50 | public override double BestKnownQuality {
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51 | get { return 0; }
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52 | }
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53 | /// <summary>
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54 | /// Gets the lower and upper bound of the function.
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55 | /// </summary>
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56 | public override DoubleMatrix Bounds {
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57 | get { return new DoubleMatrix(new double[,] { { -2.048, 2.048 } }); }
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58 | }
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59 | /// <summary>
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60 | /// Gets the minimum problem size (2).
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61 | /// </summary>
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62 | public override int MinimumProblemSize {
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63 | get { return 2; }
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64 | }
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65 | /// <summary>
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66 | /// Gets the (theoretical) maximum problem size (2^31 - 1).
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67 | /// </summary>
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68 | public override int MaximumProblemSize {
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69 | get { return int.MaxValue; }
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70 | }
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71 |
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72 | [StorableConstructor]
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73 | protected RosenbrockEvaluator(StorableConstructorFlag _) : base(_) { }
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74 | protected RosenbrockEvaluator(RosenbrockEvaluator original, Cloner cloner) : base(original, cloner) { }
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75 | public RosenbrockEvaluator() : base() { }
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76 |
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77 | public override IDeepCloneable Clone(Cloner cloner) {
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78 | return new RosenbrockEvaluator(this, cloner);
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79 | }
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80 |
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81 | public override RealVector GetBestKnownSolution(int dimension) {
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82 | if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension.");
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83 | RealVector result = new RealVector(dimension);
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84 | for (int i = 0; i < dimension; i++) result[i] = 1;
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85 | return result;
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86 | }
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87 |
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88 | /// <summary>
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89 | /// Evaluates the test function for a specific <paramref name="point"/>.
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90 | /// </summary>
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91 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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92 | /// <returns>The result value of the Rosenbrock function at the given point.</returns>
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93 | public static double Apply(RealVector point) {
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94 | double result = 0;
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95 | for (int i = 0; i < point.Length - 1; i++) {
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96 | result += 100 * (point[i] * point[i] - point[i + 1]) * (point[i] * point[i] - point[i + 1]);
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97 | result += (point[i] - 1) * (point[i] - 1);
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98 | }
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99 | return result;
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100 | }
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101 |
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102 | /// <summary>
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103 | /// Evaluates the test function for a specific <paramref name="point"/>.
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104 | /// </summary>
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105 | /// <remarks>Calls <see cref="Apply"/>.</remarks>
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106 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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107 | /// <returns>The result value of the Rosenbrock function at the given point.</returns>
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108 | public override double Evaluate(RealVector point) {
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109 | return Apply(point);
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110 | }
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111 | }
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112 | }
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