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source: branches/PTSP/HeuristicLab.Problems.PTSP/3.3/Improvers/PTSPExhaustiveInsertionLocalImprovement.cs @ 13412

Last change on this file since 13412 was 13412, checked in by abeham, 9 years ago

#2221:

  • Completely refactored PTSP branch
    • Added two sets of problem instances based on TSPLIB: homogeneous and heterogeneous
    • Implemented missing EvaluateByCoordinates for 1-shift moves
    • Made it clear that move evaluators are for estimated PTSP only
    • Changed parameter realization from a rather strange list of list of ints to a list of bool arrays
    • Reusing code of the 2-opt and 1-shift move evaluators in 2.5 move evaluator
    • Introducing distance calculators to properly handle the case when no distance matrix is given (previous code only worked with distance matrix and without only with euclidean distance in some settings)
    • Fixed several smaller code issues: protected, static, method parameters, copy & paste, interfaces, naming, parameters, serialization hooks, license headers, doc comments, data types
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 System.Threading;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.PermutationEncoding;
28using HeuristicLab.Operators;
29using HeuristicLab.Optimization;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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 inserting a city in the tour between two other cities 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, IEstimatedPTSPOperator, 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 ILookupParameter<ItemList<BoolArray>> RealizationsParameter {
77      get { return (ILookupParameter<ItemList<BoolArray>>)Parameters["Realizations"]; }
78    }
79
80    [StorableConstructor]
81    private PTSPExhaustiveInsertionLocalImprovement(bool deserializing) : base(deserializing) { }
82    private PTSPExhaustiveInsertionLocalImprovement(PTSPExhaustiveInsertionLocalImprovement original, Cloner cloner) : base(original, cloner) { }
83    public PTSPExhaustiveInsertionLocalImprovement()
84      : base() {
85      Parameters.Add(new LookupParameter<Permutation>("Permutation", "The solution as permutation."));
86      Parameters.Add(new LookupParameter<IntValue>("LocalIterations", "The number of iterations that have already been performed."));
87      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)));
88      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)."));
89      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The collection where to store results."));
90      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The quality value of the assignment."));
91      Parameters.Add(new LookupParameter<BoolValue>("Maximization", "True if the problem should be maximized or minimized."));
92      Parameters.Add(new LookupParameter<DistanceMatrix>("DistanceMatrix", "The matrix which contains the distances between the cities."));
93      Parameters.Add(new LookupParameter<ItemList<BoolArray>>("Realizations", "The list of samples drawn from all possible stochastic instances."));
94    }
95
96    public override IDeepCloneable Clone(Cloner cloner) {
97      return new PTSPExhaustiveInsertionLocalImprovement(this, cloner);
98    }
99
100    public static void Improve(Permutation assignment, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, CancellationToken cancellation, ItemList<BoolArray> realizations) {
101      var distanceM = (DistanceMatrix)distances;
102      for (var i = localIterations.Value; i < maxIterations; i++) {
103        TranslocationMove bestMove = null;
104        double bestQuality = 0; // we have to make an improvement, so 0 is the baseline
105        double evaluations = 0.0;
106        foreach (var move in ExhaustiveInsertionMoveGenerator.Generate(assignment)) {
107          double moveQuality = PTSPEstimatedInsertionMoveEvaluator.EvaluateByDistanceMatrix(assignment, move, distanceM, realizations);
108          int min = Math.Min(move.Index1, move.Index3);
109          int max = Math.Max(move.Index2, move.Index3 + (move.Index2 - move.Index1));
110          evaluations += 2.0 * (max - min + 1) / assignment.Length
111            + 4.0 * (assignment.Length - (max - min + 1)) / assignment.Length;
112          if (maximization && moveQuality > bestQuality
113            || !maximization && moveQuality < bestQuality) {
114            bestQuality = moveQuality;
115            bestMove = move;
116          }
117        }
118        evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);
119        if (bestMove == null) break;
120        TranslocationManipulator.Apply(assignment, bestMove.Index1, bestMove.Index2, bestMove.Index3);
121        quality.Value += bestQuality;
122        localIterations.Value++;
123        cancellation.ThrowIfCancellationRequested();
124      }
125    }
126
127    public override IOperation Apply() {
128      var maxIterations = MaximumIterationsParameter.ActualValue.Value;
129      var assignment = PermutationParameter.ActualValue;
130      var maximization = MaximizationParameter.ActualValue.Value;
131      var distances = DistanceMatrixParameter.ActualValue;
132      var quality = QualityParameter.ActualValue;
133      var localIterations = LocalIterationsParameter.ActualValue;
134      var evaluations = EvaluatedSolutionsParameter.ActualValue;
135      var realizations = RealizationsParameter.ActualValue;
136      if (localIterations == null) {
137        localIterations = new IntValue(0);
138        LocalIterationsParameter.ActualValue = localIterations;
139      }
140
141      Improve(assignment, distances, quality, localIterations, evaluations, maximization, maxIterations, CancellationToken, realizations);
142
143      localIterations.Value = 0;
144      return base.Apply();
145    }
146  }
147}
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