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.Persistence.Default.CompositeSerializers.Storable;


26  using HeuristicLab.Data.MoveVectorData;


27  using HeuristicLab.Encodings.MoveVectorEncoding;


28 


29  namespace HeuristicLab.Encodings.BinaryVectorEncoding {


30  /// <summary>


31  /// Uniform crossover for move vectors.


32  /// </summary>


33  /// <remarks>


34  /// It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, SpringerVerlag Berlin Heidelberg.


35  /// </remarks>


36  [Item("UniformCrossover", "Uniform crossover for move vectors. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, SpringerVerlag Berlin Heidelberg.")]


37  [StorableClass]


38  public sealed class UniformCrossover : MoveVectorCrossover


39  {


40 


41  [StorableConstructor]


42  private UniformCrossover(bool deserializing) : base(deserializing) { }


43  private UniformCrossover(UniformCrossover original, Cloner cloner) : base(original, cloner) { }


44  public UniformCrossover() : base() { }


45 


46  public override IDeepCloneable Clone(Cloner cloner) {


47  return new UniformCrossover(this, cloner);


48  }


49 


50  /// <summary>


51  /// Performs a uniform crossover between two binary vectors.


52  /// </summary>


53  /// <param name="random">A random number generator.</param>


54  /// <param name="parent1">The first parent for crossover.</param>


55  /// <param name="parent2">The second parent for crossover.</param>


56  /// <returns>The newly created binary vector, resulting from the uniform crossover.</returns>


57  public static MoveVector Apply(IRandom random, MoveVector parent1, MoveVector parent2) {


58  if (parent1.Length != parent2.Length)


59  throw new ArgumentException("UniformCrossover: The parents are of different length.");


60 


61  int length = parent1.Length;


62  MoveVector result = new MoveVector(length, parent1.MoveTypes);


63 


64  for (int i = 0; i < length; i++) {


65  if (random.NextDouble() < 0.5)


66  result[i] = parent1[i];


67  else


68  result[i] = parent2[i];


69  }


70 


71  return result;


72  }


73 


74  protected override MoveVector Cross(IRandom random, ItemArray<MoveVector> parents) {


75  if (parents.Length != 2) throw new ArgumentException("ERROR in UniformCrossover: The number of parents is not equal to 2");


76 


77  return Apply(random, parents[0], parents[1]);


78  }


79  }


80  }

