1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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 HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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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 generalized Rastrigin function y = 0.5 + (Sin^2(Sqrt(x^2 + y^2)) - 0.5) / (1 + 0.001 * (x^2 + y^2))^2 is a multimodal function that has its optimal value 0 at the origin.
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32 |
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33 | /// </summary
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34 | [Item("SchafferF6", "Evaluates the Schaffer F6 function y = 0.5 + (Sin^2(Sqrt(x^2 + y^2)) - 0.5) / (1 + 0.001 * (x^2 + y^2))^2 on a given point. The optimum of this function is 0 at the origin. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.")]
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35 | [StorableClass]
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36 | public class SchafferF6 : SingleObjectiveTestFunction {
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37 | /// <summary>
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38 | /// Returns false as the Rastrigin function is a minimization problem.
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39 | /// </summary>
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40 | public override bool Maximization {
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41 | get { return false; }
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42 | }
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43 | /// <summary>
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44 | /// Gets the optimum function value (0).
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45 | /// </summary>
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46 | public override double BestKnownQuality {
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47 | get { return 0; }
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48 | }
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49 | /// <summary>
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50 | /// Gets the lower and upper bound of the function.
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51 | /// </summary>
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52 | public override DoubleMatrix Bounds {
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53 | get { return new DoubleMatrix(new double[,] { { -100, 100 } }); }
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54 | }
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55 | /// <summary>
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56 | /// Gets the minimum problem size (2).
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57 | /// </summary>
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58 | public override int MinimumProblemSize {
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59 | get { return 2; }
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60 | }
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61 | /// <summary>
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62 | /// Gets the maximum problem size (2).
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63 | /// </summary>
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64 | public override int MaximumProblemSize {
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65 | get { return 2; }
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66 | }
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67 |
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68 | public override RealVector GetBestKnownSolution(int dimension) {
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69 | return new RealVector(dimension);
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70 | }
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71 |
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72 | [StorableConstructor]
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73 | protected SchafferF6(bool deserializing) : base(deserializing) { }
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74 | protected SchafferF6(SchafferF6 original, Cloner cloner) : base(original, cloner) { }
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75 | public SchafferF6() : base() { }
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76 |
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77 | public override IDeepCloneable Clone(Cloner cloner) {
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78 | return new SchafferF6(this, cloner);
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79 | }
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80 |
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81 | /// <summary>
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82 | /// Evaluates the test function for a specific <paramref name="point"/>.
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83 | /// </summary>
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84 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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85 | /// <returns>The result value of the Rastrigin function at the given point.</returns>
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86 | public static double Apply(RealVector point) {
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87 | if (point.Length != 2) throw new ArgumentException("The SchafferF6 can only be evaluated for two dimenional vectors");
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88 | var sumSquare = point[0] * point[0] + point[1] * point[1];
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89 | var sin = Math.Sin(Math.Sqrt(sumSquare));
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90 | var nom = sin * sin - 0.5;
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91 | var denom = (1 + 0.001 * sumSquare) * (1 + 0.001 * sumSquare);
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92 | return 0.5 + nom / denom;
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93 | }
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94 |
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95 | /// <summary>
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96 | /// Evaluates the test function for a specific <paramref name="point"/>.
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97 | /// </summary>
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98 | /// <remarks>Calls <see cref="Apply"/>.</remarks>
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99 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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100 | /// <returns>The result value of the Rastrigin function at the given point.</returns>
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101 | public override double Evaluate(RealVector point) {
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102 | return Apply(point);
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103 | }
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104 | }
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105 | }
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