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source: branches/PTSP/HeuristicLab.Problems.PTSP/3.3/Improvers/PTSPExhaustiveInsertionLocalImprovement.cs @ 12962

Last change on this file since 12962 was 12261, checked in by apolidur, 10 years ago

#2221: Fixing MoveEvaluators after running unit tests

File size: 7.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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
22using System;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.PermutationEncoding;
27using HeuristicLab.Operators;
28using HeuristicLab.Optimization;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31using System.Threading;
32
33namespace HeuristicLab.Problems.PTSP {
34  /// <summary>
35  /// An operator that improves probabilistic traveling salesman solutions.
36  /// </summary>
37  /// <remarks>
38  /// The operator tries to improve the probabilistic traveling salesman solution by swapping two randomly chosen edges for a certain number of times.
39  /// </remarks>
40  [Item("PTSPExhaustiveInsertionLocalImprovement", "An operator that improves probabilistic traveling salesman solutions. The operator tries to improve the probabilistic traveling salesman solution by swapping two randomly chosen edges for a certain number of times.")]
41  [StorableClass]
42  public sealed class PTSPExhaustiveInsertionLocalImprovement : SingleSuccessorOperator, ILocalImprovementOperator {
43 
44    public ILookupParameter<IntValue> LocalIterationsParameter {
45      get { return (ILookupParameter<IntValue>)Parameters["LocalIterations"]; }
46    }
47
48    public IValueLookupParameter<IntValue> MaximumIterationsParameter {
49      get { return (IValueLookupParameter<IntValue>)Parameters["MaximumIterations"]; }
50    }
51
52    public ILookupParameter<IntValue> EvaluatedSolutionsParameter {
53      get { return (ILookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
54    }
55
56    public ILookupParameter<ResultCollection> ResultsParameter {
57      get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
58    }
59
60    public ILookupParameter<Permutation> PermutationParameter {
61      get { return (ILookupParameter<Permutation>)Parameters["Permutation"]; }
62    }
63
64    public ILookupParameter<DoubleValue> QualityParameter {
65      get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
66    }
67
68    public ILookupParameter<BoolValue> MaximizationParameter {
69      get { return (ILookupParameter<BoolValue>)Parameters["Maximization"]; }
70    }
71
72    public ILookupParameter<DistanceMatrix> DistanceMatrixParameter {
73      get { return (ILookupParameter<DistanceMatrix>)Parameters["DistanceMatrix"]; }
74    }
75
76    public IValueParameter<ItemList<ItemList<IntValue>>> RealizationsParameter {
77      get { return (IValueParameter<ItemList<ItemList<IntValue>>>)Parameters["Realizations"]; }
78    }
79
80    [StorableConstructor]
81    protected PTSPExhaustiveInsertionLocalImprovement(bool deserializing) : base(deserializing) { }
82    protected PTSPExhaustiveInsertionLocalImprovement(PTSPExhaustiveInsertionLocalImprovement original, Cloner cloner)
83      : base(original, cloner) {
84    }
85    public PTSPExhaustiveInsertionLocalImprovement()
86      : base() {
87      Parameters.Add(new LookupParameter<Permutation>("Permutation", "The solution as permutation."));
88      Parameters.Add(new LookupParameter<IntValue>("LocalIterations", "The number of iterations that have already been performed."));
89      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)));
90      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)."));
91      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The collection where to store results."));
92      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The quality value of the assignment."));
93      Parameters.Add(new LookupParameter<BoolValue>("Maximization", "True if the problem should be maximized or minimized."));
94      Parameters.Add(new LookupParameter<DistanceMatrix>("DistanceMatrix", "The matrix which contains the distances between the cities."));
95      Parameters.Add(new ValueParameter<ItemList<ItemList<IntValue>>>("Realizations", "The concrete..."));
96    }
97
98    public override IDeepCloneable Clone(Cloner cloner) {
99      return new PTSPExhaustiveInsertionLocalImprovement(this, cloner);
100    }
101
102    public static void Improve(Permutation assignment, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, CancellationToken cancellation, ItemList<ItemList<IntValue>> realizations) {
103      DistanceMatrix distanceM = (DistanceMatrix)distances;
104      for (int i = localIterations.Value; i < maxIterations; i++) {
105        TranslocationMove bestMove = null;
106        double bestQuality = 0; // we have to make an improvement, so 0 is the baseline
107        double evaluations = 0.0;
108        foreach (var move in ExhaustiveInsertionMoveGenerator.Generate(assignment)) {
109          double moveQuality = PTSPEstimatedInsertionEvaluator.EvaluateByDistanceMatrix(assignment, move, distanceM, realizations);
110          int min = Math.Min(move.Index1, move.Index3);
111          int max = Math.Max(move.Index2, move.Index3 + (move.Index2 - move.Index1));
112          evaluations += 2.0 * (max - min + 1) / assignment.Length
113            + 4.0 * (assignment.Length - (max - min + 1)) / assignment.Length;
114          if (maximization && moveQuality > bestQuality
115            || !maximization && moveQuality < bestQuality) {
116            bestQuality = moveQuality;
117            bestMove = move;
118          }
119        }
120        evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);
121        if (bestMove == null) break;
122        TranslocationManipulator.Apply(assignment, bestMove.Index1, bestMove.Index2, bestMove.Index3);
123        quality.Value += bestQuality;
124        localIterations.Value++;
125        cancellation.ThrowIfCancellationRequested();
126      }
127    }
128
129    public override IOperation Apply() {
130      var maxIterations = MaximumIterationsParameter.ActualValue.Value;
131      var assignment = PermutationParameter.ActualValue;
132      var maximization = MaximizationParameter.ActualValue.Value;
133      var distances = DistanceMatrixParameter.ActualValue;
134      var quality = QualityParameter.ActualValue;
135      var localIterations = LocalIterationsParameter.ActualValue;
136      var evaluations = EvaluatedSolutionsParameter.ActualValue;
137      var realizations = RealizationsParameter.Value;
138      if (localIterations == null) {
139        localIterations = new IntValue(0);
140        LocalIterationsParameter.ActualValue = localIterations;
141      }
142
143      Improve(assignment, distances, quality, localIterations, evaluations, maximization, maxIterations, CancellationToken, realizations);
144
145      localIterations.Value = 0;
146      return base.Apply();
147    }
148  }
149}
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