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 HeuristicLab.Common;


23  using HeuristicLab.Core;


24  using HeuristicLab.Data;


25  using HeuristicLab.Encodings.RealVectorEncoding;


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


27 


28  namespace HeuristicLab.Problems.TestFunctions {


29  /// <summary>


30  /// Base class for a test function evaluator.


31  /// </summary>


32  [Item("SingleObjective Function", "Base class for single objective functions.")]


33  [StorableClass]


34  public abstract class SingleObjectiveTestFunction : ParameterizedNamedItem, ISingleObjectiveTestFunction {


35  /// <summary>


36  /// These operators should not change their name through the GUI


37  /// </summary>


38  public override bool CanChangeName {


39  get { return false; }


40  }


41  /// <summary>


42  /// Returns whether the actual function constitutes a maximization or minimization problem.


43  /// </summary>


44  public abstract bool Maximization { get; }


45  /// <summary>


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


47  /// </summary>


48  public abstract DoubleMatrix Bounds { get; }


49  /// <summary>


50  /// Gets the optimum function value.


51  /// </summary>


52  public abstract double BestKnownQuality { get; }


53  /// <summary>


54  /// Gets the minimum problem size.


55  /// </summary>


56  public abstract int MinimumProblemSize { get; }


57  /// <summary>


58  /// Gets the maximum problem size.


59  /// </summary>


60  public abstract int MaximumProblemSize { get; }


61 


62  [StorableConstructor]


63  protected SingleObjectiveTestFunction(bool deserializing) : base(deserializing) { }


64  protected SingleObjectiveTestFunction(SingleObjectiveTestFunction original, Cloner cloner) : base(original, cloner) { }


65  protected SingleObjectiveTestFunction() : base() { }


66 


67  public virtual double Evaluate2D(double x, double y) {


68  return Evaluate(new RealVector(new double[] { x, y }));


69  }


70 


71  /// <summary>


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


73  /// </summary>


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


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


76  public abstract double Evaluate(RealVector point);


77 


78  /// <summary>


79  /// Gets the best known solution for this function.


80  /// </summary>


81  public abstract RealVector GetBestKnownSolution(int dimension);


82  }


83  }

