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 System.Threading;


24  using HeuristicLab.Common;


25  using HeuristicLab.Core;


26  using HeuristicLab.Data;


27  using HeuristicLab.Encodings.PermutationEncoding;


28  using HeuristicLab.Operators;


29  using HeuristicLab.Optimization;


30  using HeuristicLab.Parameters;


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


32 


33  namespace HeuristicLab.Problems.QuadraticAssignment {


34  [Item("QAPStochasticScrambleLocalImprovement", "Takes a solution and finds the local optimum with respect to the scramble neighborhood by decending along the steepest gradient.")]


35  [StorableClass]


36  public class QAPStochasticScrambleLocalImprovement : SingleSuccessorOperator, ILocalImprovementOperator, IStochasticOperator, ISingleObjectiveOperator {


37 


38  public ILookupParameter<IntValue> LocalIterationsParameter {


39  get { return (ILookupParameter<IntValue>)Parameters["LocalIterations"]; }


40  }


41 


42  public ILookupParameter<IRandom> RandomParameter {


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


44  }


45 


46  public IValueLookupParameter<IntValue> MaximumIterationsParameter {


47  get { return (IValueLookupParameter<IntValue>)Parameters["MaximumIterations"]; }


48  }


49 


50  public ILookupParameter<IntValue> EvaluatedSolutionsParameter {


51  get { return (ILookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }


52  }


53 


54  public ILookupParameter<ResultCollection> ResultsParameter {


55  get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }


56  }


57 


58  public ILookupParameter<Permutation> AssignmentParameter {


59  get { return (ILookupParameter<Permutation>)Parameters["Assignment"]; }


60  }


61 


62  public ILookupParameter<DoubleValue> QualityParameter {


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


64  }


65 


66  public ILookupParameter<BoolValue> MaximizationParameter {


67  get { return (ILookupParameter<BoolValue>)Parameters["Maximization"]; }


68  }


69 


70  public ILookupParameter<DoubleMatrix> WeightsParameter {


71  get { return (ILookupParameter<DoubleMatrix>)Parameters["Weights"]; }


72  }


73 


74  public ILookupParameter<DoubleMatrix> DistancesParameter {


75  get { return (ILookupParameter<DoubleMatrix>)Parameters["Distances"]; }


76  }


77 


78  public IValueLookupParameter<IntValue> NeighborhoodSizeParameter {


79  get { return (IValueLookupParameter<IntValue>)Parameters["NeighborhoodSize"]; }


80  }


81 


82  [StorableConstructor]


83  protected QAPStochasticScrambleLocalImprovement(bool deserializing) : base(deserializing) { }


84  protected QAPStochasticScrambleLocalImprovement(QAPStochasticScrambleLocalImprovement original, Cloner cloner)


85  : base(original, cloner) {


86  }


87  public QAPStochasticScrambleLocalImprovement()


88  : base() {


89  Parameters.Add(new LookupParameter<IntValue>("LocalIterations", "The number of iterations that have already been performed."));


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


91  Parameters.Add(new ValueLookupParameter<IntValue>("MaximumIterations", "The maximum amount of iterations that should be performed (note that this operator will abort earlier when a local optimum is reached).", new IntValue(10000)));


92  Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The amount of evaluated solutions (here a move is counted only as 4/n evaluated solutions with n being the length of the permutation)."));


93  Parameters.Add(new LookupParameter<ResultCollection>("Results", "The collection where to store results."));


94  Parameters.Add(new LookupParameter<Permutation>("Assignment", "The permutation that is to be locally optimized."));


95  Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The quality value of the assignment."));


96  Parameters.Add(new LookupParameter<BoolValue>("Maximization", "True if the problem should be maximized or minimized."));


97  Parameters.Add(new LookupParameter<DoubleMatrix>("Weights", "The weights matrix."));


98  Parameters.Add(new LookupParameter<DoubleMatrix>("Distances", "The distances matrix."));


99  Parameters.Add(new ValueLookupParameter<IntValue>("NeighborhoodSize", "The number of moves to sample from the neighborhood.", new IntValue(100)));


100  }


101 


102  public override IDeepCloneable Clone(Cloner cloner) {


103  return new QAPStochasticScrambleLocalImprovement(this, cloner);


104  }


105 


106  public static void Improve(IRandom random, Permutation assignment, DoubleMatrix weights, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, int neighborhoodSize, CancellationToken cancellation) {


107  for (int i = localIterations.Value; i < maxIterations; i++) {


108  ScrambleMove bestMove = null;


109  double bestQuality = 0; // we have to make an improvement, so 0 is the baseline


110  double evaluations = 0.0;


111  for (int j = 0; j < neighborhoodSize; j++) {


112  var move = StochasticScrambleMultiMoveGenerator.GenerateRandomMove(assignment, random);


113  double moveQuality = QAPScrambleMoveEvaluator.Apply(assignment, move, weights, distances);


114  evaluations += 2.0 * move.ScrambledIndices.Length / assignment.Length;


115  if (maximization && moveQuality > bestQuality


116   !maximization && moveQuality < bestQuality) {


117  bestQuality = moveQuality;


118  bestMove = move;


119  }


120  }


121  evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);


122  if (bestMove == null) break;


123  ScrambleManipulator.Apply(assignment, bestMove.StartIndex, bestMove.ScrambledIndices);


124  quality.Value += bestQuality;


125  localIterations.Value++;


126  cancellation.ThrowIfCancellationRequested();


127  }


128  }


129 


130  public override IOperation Apply() {


131  var random = RandomParameter.ActualValue;


132  var maxIterations = MaximumIterationsParameter.ActualValue.Value;


133  var neighborhoodSize = NeighborhoodSizeParameter.ActualValue.Value;


134  var assignment = AssignmentParameter.ActualValue;


135  var maximization = MaximizationParameter.ActualValue.Value;


136  var weights = WeightsParameter.ActualValue;


137  var distances = DistancesParameter.ActualValue;


138  var quality = QualityParameter.ActualValue;


139  var localIterations = LocalIterationsParameter.ActualValue;


140  var evaluations = EvaluatedSolutionsParameter.ActualValue;


141  if (localIterations == null) {


142  localIterations = new IntValue(0);


143  LocalIterationsParameter.ActualValue = localIterations;


144  }


145 


146  Improve(random, assignment, weights, distances, quality, localIterations, evaluations, maximization, maxIterations, neighborhoodSize, CancellationToken);


147 


148  localIterations.Value = 0;


149  return base.Apply();


150  }


151  }


152  }

