1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022018 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 System.Collections.Generic;


24  using HeuristicLab.Common;


25  using HeuristicLab.Core;


26  using HeuristicLab.Data;


27  using HeuristicLab.Optimization;


28  using HeuristicLab.Parameters;


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


30 


31  namespace HeuristicLab.Encodings.PermutationEncoding {


32  [Item("StochasticInsertionMultiMoveGenerator", "Generates all possible insertion moves (3opt) from a few numbers in a given permutation.")]


33  [StorableClass]


34  public class StochasticInsertionMultiMoveGenerator : TranslocationMoveGenerator, IMultiMoveGenerator, IStochasticOperator {


35  public ILookupParameter<IRandom> RandomParameter {


36  get { return (ILookupParameter<IRandom>)Parameters["Random"]; }


37  }


38  public IValueLookupParameter<IntValue> SampleSizeParameter {


39  get { return (IValueLookupParameter<IntValue>)Parameters["SampleSize"]; }


40  }


41 


42  public IntValue SampleSize {


43  get { return SampleSizeParameter.Value; }


44  set { SampleSizeParameter.Value = value; }


45  }


46 


47  [StorableConstructor]


48  protected StochasticInsertionMultiMoveGenerator(bool deserializing) : base(deserializing) { }


49  protected StochasticInsertionMultiMoveGenerator(StochasticInsertionMultiMoveGenerator original, Cloner cloner) : base(original, cloner) { }


50  public StochasticInsertionMultiMoveGenerator() : base() {


51  Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));


52  Parameters.Add(new ValueLookupParameter<IntValue>("SampleSize", "The number of moves to generate."));


53  }


54 


55  public override IDeepCloneable Clone(Cloner cloner) {


56  return new StochasticInsertionMultiMoveGenerator(this, cloner);


57  }


58 


59  public static TranslocationMove[] Apply(Permutation permutation, IRandom random, int sampleSize) {


60  int length = permutation.Length;


61  if (length == 1) throw new ArgumentException("ExhaustiveSingleInsertionMoveGenerator: There cannot be an insertion move given a permutation of length 1.", "permutation");


62  TranslocationMove[] moves = new TranslocationMove[sampleSize];


63  int count = 0;


64  HashSet<int> usedIndices = new HashSet<int>();


65  while (count < sampleSize) {


66 


67  int index = random.Next(length);


68 


69  if (usedIndices.Count != length)


70  while (usedIndices.Contains(index))


71  index = random.Next(length);


72  usedIndices.Add(index);


73 


74  if (permutation.PermutationType == PermutationTypes.Absolute) {


75  for (int j = 1; j <= length  1; j++) {


76  moves[count++] = new TranslocationMove(index, index, (index + j) % length);


77  if (count == sampleSize) break;


78  }


79  } else {


80  if (length > 2) {


81  for (int j = 1; j < length  1; j++) {


82  int insertPoint = (index + j) % length;


83  if (index + j >= length) insertPoint++;


84  moves[count++] = new TranslocationMove(index, index, insertPoint);


85  if (count == sampleSize) break;


86  }


87  } else { // doesn't make sense, but just create a dummy move to not crash the algorithms


88  moves = new TranslocationMove[1];


89  moves[0] = new TranslocationMove(0, 0, 1);


90  count = sampleSize;


91  }


92  }


93  }


94  return moves;


95  }


96 


97  protected override TranslocationMove[] GenerateMoves(Permutation permutation) {


98  IRandom random = RandomParameter.ActualValue;


99  if (random == null) throw new InvalidOperationException(Name + ": No random number generator found.");


100  return Apply(permutation, random, SampleSizeParameter.ActualValue.Value);


101  }


102  }


103  }

