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.Optimization;


27  using HeuristicLab.Parameters;


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


29 


30  namespace HeuristicLab.Encodings.IntegerVectorEncoding {


31  /// <summary>


32  /// Heuristic crossover for integer vectors: Calculates the vector from the worse to the better parent and adds that to the better parent weighted with a factor in the interval [0;1).


33  /// The result is then rounded to the next feasible integer.


34  /// The idea is that going further in direction from the worse to the better leads to even better solutions (naturally this depends on the fitness landscape).


35  /// </summary>


36  [Item("RoundedHeuristicCrossover", "The heuristic crossover produces offspring that extend the better parent in direction from the worse to the better parent.")]


37  [StorableClass]


38  public class RoundedHeuristicCrossover : BoundedIntegerVectorCrossover, ISingleObjectiveOperator {


39  /// <summary>


40  /// Whether the problem is a maximization or minimization problem.


41  /// </summary>


42  public ValueLookupParameter<BoolValue> MaximizationParameter {


43  get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }


44  }


45  /// <summary>


46  /// The quality of the parents.


47  /// </summary>


48  public ScopeTreeLookupParameter<DoubleValue> QualityParameter {


49  get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }


50  }


51 


52  [StorableConstructor]


53  protected RoundedHeuristicCrossover(bool deserializing) : base(deserializing) { }


54  protected RoundedHeuristicCrossover(RoundedHeuristicCrossover original, Cloner cloner) : base(original, cloner) { }


55  /// <summary>


56  /// Initializes a new instance of <see cref="RoundedHeuristicCrossover"/> with two variable infos


57  /// (<c>Maximization</c> and <c>Quality</c>).


58  /// </summary>


59  public RoundedHeuristicCrossover()


60  : base() {


61  Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "Whether the problem is a maximization problem or not."));


62  Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality values of the parents."));


63  }


64 


65  public override IDeepCloneable Clone(Cloner cloner) {


66  return new RoundedHeuristicCrossover(this, cloner);


67  }


68 


69  /// <summary>


70  /// Perfomrs a heuristic crossover on the two given parents.


71  /// </summary>


72  /// <exception cref="ArgumentException">Thrown when two parents are not of the same length.</exception>


73  /// <param name="random">The random number generator.</param>


74  /// <param name="betterParent">The first parent for the crossover operation.</param>


75  /// <param name="worseParent">The second parent for the crossover operation.</param>


76  /// <param name="bounds">The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).</param>


77  /// <returns>The newly created integer vector, resulting from the heuristic crossover.</returns>


78  public static IntegerVector Apply(IRandom random, IntegerVector betterParent, IntegerVector worseParent, IntMatrix bounds) {


79  if (betterParent.Length != worseParent.Length)


80  throw new ArgumentException("HeuristicCrossover: the two parents are not of the same length");


81 


82  int length = betterParent.Length;


83  var result = new IntegerVector(length);


84  double factor = random.NextDouble();


85 


86  int min, max, step = 1;


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


88  min = bounds[i % bounds.Rows, 0];


89  max = bounds[i % bounds.Rows, 1];


90  if (bounds.Columns > 2) step = bounds[i % bounds.Rows, 2];


91  max = FloorFeasible(min, max, step, max  1);


92  result[i] = RoundFeasible(min, max, step, betterParent[i] + factor * (betterParent[i]  worseParent[i]));


93  }


94  return result;


95  }


96 


97  /// <summary>


98  /// Performs a heuristic crossover operation for two given parent integer vectors.


99  /// </summary>


100  /// <exception cref="ArgumentException">Thrown when the number of parents is not equal to 2.</exception>


101  /// <exception cref="InvalidOperationException">


102  /// Thrown when either:<br/>


103  /// <list type="bullet">


104  /// <item><description>Maximization parameter could not be found.</description></item>


105  /// <item><description>Quality parameter could not be found or the number of quality values is not equal to the number of parents.</description></item>


106  /// </list>


107  /// </exception>


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


109  /// <param name="parents">An array containing the two real vectors that should be crossed.</param>


110  /// /// <param name="bounds">The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).</param>


111  /// <returns>The newly created integer vector, resulting from the crossover operation.</returns>


112  protected override IntegerVector CrossBounded(IRandom random, ItemArray<IntegerVector> parents, IntMatrix bounds) {


113  if (parents.Length != 2) throw new ArgumentException("RoundedHeuristicCrossover: The number of parents is not equal to 2");


114 


115  if (MaximizationParameter.ActualValue == null) throw new InvalidOperationException("RoundedHeuristicCrossover: Parameter " + MaximizationParameter.ActualName + " could not be found.");


116  if (QualityParameter.ActualValue == null  QualityParameter.ActualValue.Length != parents.Length) throw new InvalidOperationException("RoundedHeuristicCrossover: Parameter " + QualityParameter.ActualName + " could not be found, or not in the same quantity as there are parents.");


117 


118  ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;


119  bool maximization = MaximizationParameter.ActualValue.Value;


120 


121  if (maximization && qualities[0].Value >= qualities[1].Value  !maximization && qualities[0].Value <= qualities[1].Value)


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


123  else


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


125  }


126  }


127  }

