1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022013 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.Operators;


27  using HeuristicLab.Parameters;


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


29 


30  namespace HeuristicLab.Problems.TestFunctions {


31  /// <summary>


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


33  /// </summary>


34  [Item("Evaluator", "Base calls for single objective test function evaluators.")]


35  [StorableClass]


36  public abstract class SingleObjectiveTestFunctionProblemEvaluator : SingleSuccessorOperator, ISingleObjectiveTestFunctionProblemEvaluator {


37  /// <summary>


38  /// The name of the function


39  /// </summary>


40  public abstract string FunctionName { get; }


41  /// <summary>


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


43  /// </summary>


44  public override bool CanChangeName {


45  get { return false; }


46  }


47  /// <summary>


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


49  /// </summary>


50  public abstract bool Maximization { get; }


51  /// <summary>


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


53  /// </summary>


54  public abstract DoubleMatrix Bounds { get; }


55  /// <summary>


56  /// Gets the optimum function value.


57  /// </summary>


58  public abstract double BestKnownQuality { get; }


59  /// <summary>


60  /// Gets the minimum problem size.


61  /// </summary>


62  public abstract int MinimumProblemSize { get; }


63  /// <summary>


64  /// Gets the maximum problem size.


65  /// </summary>


66  public abstract int MaximumProblemSize { get; }


67 


68  public ILookupParameter<DoubleValue> QualityParameter {


69  get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }


70  }


71  public ILookupParameter<RealVector> PointParameter {


72  get { return (ILookupParameter<RealVector>)Parameters["Point"]; }


73  }


74 


75  [StorableConstructor]


76  protected SingleObjectiveTestFunctionProblemEvaluator(bool deserializing) : base(deserializing) { }


77  protected SingleObjectiveTestFunctionProblemEvaluator(SingleObjectiveTestFunctionProblemEvaluator original, Cloner cloner) : base(original, cloner) { }


78  /// <summary>


79  /// Initializes a new instance of <see cref="SingleObjectiveTestFunctionEvaluator"/> with two parameters


80  /// (<c>Quality</c> and <c>Point</c>).


81  /// </summary>


82  public SingleObjectiveTestFunctionProblemEvaluator()


83  : base() {


84  Parameters.Add(new LookupParameter<DoubleValue>("Quality", "Result of the evaluation of a solution."));


85  Parameters.Add(new LookupParameter<RealVector>("Point", "The point at which the function should be evaluated."));


86  }


87 


88  public override IOperation Apply() {


89  RealVector point = PointParameter.ActualValue;


90  double quality = Evaluate(point);


91  QualityParameter.ActualValue = new DoubleValue(quality);


92  return base.Apply();


93  }


94 


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


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


97  }


98 


99  /// <summary>


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


101  /// </summary>


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


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


104  public abstract double Evaluate(RealVector point);


105 


106  /// <summary>


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


108  /// </summary>


109  public abstract RealVector GetBestKnownSolution(int dimension);


110  }


111  }

