1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022015 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 


22  using System;


23  using HeuristicLab.Common;


24  using HeuristicLab.Core;


25  using HeuristicLab.Data;


26  using HeuristicLab.Encodings.RealVectorEncoding;


27  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;


28 


29  namespace HeuristicLab.Problems.TestFunctions {


30  /// <summary>


31  /// The Schwefel function (sine root) is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New SelfAdaptive Selection Scheme for Genetic Algorithms. Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218221, Springer.


32  /// </summary>


33  [Item("Schwefel", "Evaluates the Schwefel function (sine root) on a given point. In the given bounds [500;500] the optimum of this function is close to 0 at (420.968746453712,420.968746453712,...,420.968746453712). It is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New SelfAdaptive Selection Scheme for Genetic Algorithms. Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218221, Springer.")]


34  [StorableClass]


35  public class Schwefel : SingleObjectiveTestFunction {


36  /// <summary>


37  /// Returns false as the Schwefel (sine root) function is a minimization problem.


38  /// </summary>


39  public override bool Maximization {


40  get { return false; }


41  }


42  /// <summary>


43  /// Gets the optimum function value (0).


44  /// </summary>


45  public override double BestKnownQuality {


46  get { return 0; }


47  }


48  /// <summary>


49  /// Gets the lower and upper bound of the function.


50  /// </summary>


51  public override DoubleMatrix Bounds {


52  get { return new DoubleMatrix(new double[,] { { 500, 500 } }); }


53  }


54  /// <summary>


55  /// Gets the minimum problem size (1).


56  /// </summary>


57  public override int MinimumProblemSize {


58  get { return 1; }


59  }


60  /// <summary>


61  /// Gets the (theoretical) maximum problem size (2^31  1).


62  /// </summary>


63  public override int MaximumProblemSize {


64  get { return int.MaxValue; }


65  }


66 


67  [StorableConstructor]


68  protected Schwefel(bool deserializing) : base(deserializing) { }


69  protected Schwefel(Schwefel original, Cloner cloner) : base(original, cloner) { }


70  public Schwefel() : base() { }


71 


72  public override IDeepCloneable Clone(Cloner cloner) {


73  return new Schwefel(this, cloner);


74  }


75 


76  public override RealVector GetBestKnownSolution(int dimension) {


77  return null;


78  }


79 


80  /// <summary>


81  /// Evaluates the test function for a specific <paramref name="point"/>.


82  /// </summary>


83  /// <param name="point">Ndimensional point for which the test function should be evaluated.</param>


84  /// <returns>The result value of the Schwefel function at the given point.</returns>


85  public static double Apply(RealVector point) {


86  double result = 418.982887272433 * point.Length;


87  for (int i = 0; i < point.Length; i++)


88  result = point[i] * Math.Sin(Math.Sqrt(Math.Abs(point[i])));


89  return (result);


90  }


91 


92  /// <summary>


93  /// Evaluates the test function for a specific <paramref name="point"/>.


94  /// </summary>


95  /// <remarks>Calls <see cref="Apply"/>.</remarks>


96  /// <param name="point">Ndimensional point for which the test function should be evaluated.</param>


97  /// <returns>The result value of the Schwefel function at the given point.</returns>


98  public override double Evaluate(RealVector point) {


99  return Apply(point);


100  }


101  }


102  }

