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source: stable/HeuristicLab.Problems.PTSP/3.3/Improvers/PTSPAnalyticalInversionLocalImprovement.cs @ 15298

Last change on this file since 15298 was 14186, checked in by swagner, 8 years ago

#2526: Updated year of copyrights in license headers

File size: 7.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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 swapping two randomly chosen edges for a certain number of times.
39  /// </remarks>
40  [Item("PTSP Analytical Inversion Local Improvement", "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 PTSPAnalyticalInversionLocalImprovement : SingleSuccessorOperator, IAnalyticalPTSPOperator, 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<DoubleArray> ProbabilitiesParameter {
77      get { return (ILookupParameter<DoubleArray>)Parameters["Probabilities"]; }
78    }
79
80    [StorableConstructor]
81    private PTSPAnalyticalInversionLocalImprovement(bool deserializing) : base(deserializing) { }
82    private PTSPAnalyticalInversionLocalImprovement(PTSPAnalyticalInversionLocalImprovement original, Cloner cloner) : base(original, cloner) { }
83    public PTSPAnalyticalInversionLocalImprovement()
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<DoubleArray>("Probabilities", "The list of probabilities of the cities to appear."));
94    }
95
96    public override IDeepCloneable Clone(Cloner cloner) {
97      return new PTSPAnalyticalInversionLocalImprovement(this, cloner);
98    }
99
100    public static void Improve(Permutation assignment, DoubleMatrix distances, DoubleValue quality, IntValue localIterations, IntValue evaluatedSolutions, bool maximization, int maxIterations, DoubleArray probabilities, CancellationToken cancellation) {
101      var distanceM = (DistanceMatrix)distances;
102      Func<int, int, double> distance = (a, b) => distanceM[a, b];
103      for (var i = localIterations.Value; i < maxIterations; i++) {
104        InversionMove bestMove = null;
105        var bestQuality = quality.Value; // we have to make an improvement, so current quality is the baseline
106        var evaluations = 0.0;
107        foreach (var move in ExhaustiveInversionMoveGenerator.Generate(assignment)) {
108          var moveQuality = PTSPAnalyticalInversionMoveEvaluator.EvaluateMove(assignment, move, distance, probabilities);
109          evaluations++;
110          if (maximization && moveQuality > bestQuality
111            || !maximization && moveQuality < bestQuality) {
112            bestQuality = moveQuality;
113            bestMove = move;
114          }
115        }
116        evaluatedSolutions.Value += (int)Math.Ceiling(evaluations);
117        if (bestMove == null) break;
118        InversionManipulator.Apply(assignment, bestMove.Index1, bestMove.Index2);
119        quality.Value = bestQuality;
120        localIterations.Value++;
121        cancellation.ThrowIfCancellationRequested();
122      }
123    }
124
125    public override IOperation Apply() {
126      var maxIterations = MaximumIterationsParameter.ActualValue.Value;
127      var assignment = PermutationParameter.ActualValue;
128      var maximization = MaximizationParameter.ActualValue.Value;
129      var distances = DistanceMatrixParameter.ActualValue;
130      var quality = QualityParameter.ActualValue;
131      var localIterations = LocalIterationsParameter.ActualValue;
132      var evaluations = EvaluatedSolutionsParameter.ActualValue;
133      var probabilities = ProbabilitiesParameter.ActualValue;
134      if (localIterations == null) {
135        localIterations = new IntValue(0);
136        LocalIterationsParameter.ActualValue = localIterations;
137      }
138
139      Improve(assignment, distances, quality, localIterations, evaluations, maximization, maxIterations, probabilities, CancellationToken);
140
141      localIterations.Value = 0;
142      return base.Apply();
143    }
144  }
145}
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