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source: branches/2521_ProblemRefactoring/HeuristicLab.Problems.PTSP/3.3/ProbabilisticTSP.cs @ 17264

Last change on this file since 17264 was 17264, checked in by abeham, 5 years ago

#2521: Finished refactoring pTSP
File size: 8.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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.Linq;
24using HEAL.Attic;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.PermutationEncoding;
29using HeuristicLab.Optimization;
30using HeuristicLab.Parameters;
31using HeuristicLab.Problems.Instances;
32using HeuristicLab.Problems.TravelingSalesman;
33using HeuristicLab.Random;
34
35namespace HeuristicLab.Problems.PTSP {
36  [Item("Probabilistic TSP (pTSP)", "Represents a Probabilistic Traveling Salesman Problem.")]
37  [StorableType("86041a8c-14e6-46e1-b20f-566892c871f6")]
38  public abstract class ProbabilisticTSP : PermutationProblem,
39      IProblemInstanceConsumer<PTSPData> {
40    protected bool SuppressEvents { get; set; }
41
42    public static int DistanceMatrixSizeLimit = 1000;
43
44    #region Parameter Properties
45    [Storable] public ValueParameter<IProbabilisticTSPData> PTSPDataParameter { get; private set; }
46    [Storable] public OptionalValueParameter<IProbabilisticTSPSolution> BestKnownSolutionParameter { get; private set; }
47    #endregion
48
49    #region Properties
50    public IProbabilisticTSPData ProbabilisticTSPData {
51      get { return PTSPDataParameter.Value; }
52      set { PTSPDataParameter.Value = value; }
53    }
54    public IProbabilisticTSPSolution BestKnownSolution {
55      get { return BestKnownSolutionParameter.Value; }
56      set { BestKnownSolutionParameter.Value = value; }
57    }
58    #endregion
59
60    public override bool Maximization {
61      get { return false; }
62    }
63
64    [StorableConstructor]
65    protected ProbabilisticTSP(StorableConstructorFlag _) : base(_) { }
66    protected ProbabilisticTSP(ProbabilisticTSP original, Cloner cloner)
67      : base(original, cloner) {
68      PTSPDataParameter = cloner.Clone(original.PTSPDataParameter);
69      BestKnownSolutionParameter = cloner.Clone(original.BestKnownSolutionParameter);
70    }
71    protected ProbabilisticTSP() : base(new PermutationEncoding("Tour")) {
72      Parameters.Add(PTSPDataParameter = new ValueParameter<IProbabilisticTSPData>("PTSP Data", "The main parameters for the pTSP."));
73      Parameters.Add(BestKnownSolutionParameter = new OptionalValueParameter<IProbabilisticTSPSolution>("BestKnownSolution", "The best known solution of this pTSP instance."));
74
75      ProbabilisticTSPData = new MatrixPTSPData();
76      Encoding.Length = ProbabilisticTSPData.Cities;
77    }
78
79    protected override void OnEncodingChanged() {
80      base.OnEncodingChanged();
81      Encoding.Length = ProbabilisticTSPData.Cities;
82    }
83
84    public override void Analyze(Permutation[] solutions, double[] qualities, ResultCollection results, IRandom random) {
85      base.Analyze(solutions, qualities, results, random);
86      var max = Maximization;
87
88      var i = !max ? qualities.Select((x, index) => new { index, Quality = x }).OrderBy(x => x.Quality).First().index
89                   : qualities.Select((x, index) => new { index, Quality = x }).OrderByDescending(x => x.Quality).First().index;
90
91      if (double.IsNaN(BestKnownQuality) ||
92          max && qualities[i] > BestKnownQuality ||
93          !max && qualities[i] < BestKnownQuality) {
94        BestKnownQuality = qualities[i];
95        BestKnownSolution = ProbabilisticTSPData.GetSolution((Permutation)solutions[i].Clone(), qualities[i]);
96      }
97
98      IResult bestSolutionResult;
99      if (results.TryGetValue("Best pTSP Solution", out bestSolutionResult)) {
100        var bestSolution = bestSolutionResult.Value as ITSPSolution;
101        if (bestSolution == null || Maximization && bestSolution.TourLength.Value < qualities[i]
102          || !Maximization && bestSolution.TourLength.Value > qualities[i]) {
103          bestSolutionResult.Value = ProbabilisticTSPData.GetSolution(solutions[i], qualities[i]);
104        }
105      } else results.Add(new Result("Best pTSP Solution", ProbabilisticTSPData.GetSolution(solutions[i], qualities[i])));
106    }
107
108    public virtual void Load(PTSPData data) {
109      if (data.Coordinates == null && data.Distances == null)
110        throw new System.IO.InvalidDataException("The given instance specifies neither coordinates nor distances!");
111      if (data.Dimension > DistanceMatrixSizeLimit && (data.DistanceMeasure == DistanceMeasure.Att
112        || data.DistanceMeasure == DistanceMeasure.Manhattan
113        || data.DistanceMeasure == DistanceMeasure.Maximum))
114        throw new System.IO.InvalidDataException("The given instance uses an unsupported distance measure and is too large for using a distance matrix.");
115      if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2)
116        throw new System.IO.InvalidDataException("The coordinates of the given instance are not in the right format, there need to be one row for each customer and two columns for the x and y coordinates.");
117
118      Encoding.Length = data.Dimension;
119      Name = data.Name;
120      Description = data.Description;
121
122      if (data.Dimension <= DistanceMatrixSizeLimit) {
123        ProbabilisticTSPData = new MatrixPTSPData(data.Name, data.GetDistanceMatrix(), data.Probabilities, data.Coordinates) { Description = data.Description };
124      } else if (data.DistanceMeasure == DistanceMeasure.Direct && data.Distances != null) {
125        ProbabilisticTSPData = new MatrixPTSPData(data.Name, data.Distances, data.Probabilities, data.Coordinates) { Description = data.Description };
126      } else {
127        switch (data.DistanceMeasure) {
128          case DistanceMeasure.Att:
129            ProbabilisticTSPData = new AttPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
130            break;
131          case DistanceMeasure.Euclidean:
132            ProbabilisticTSPData = new EuclideanPTSPData(data.Name, data.Coordinates, data.Probabilities, EuclideanTSPData.DistanceRounding.None) { Description = data.Description };
133            break;
134          case DistanceMeasure.RoundedEuclidean:
135            ProbabilisticTSPData = new EuclideanPTSPData(data.Name, data.Coordinates, data.Probabilities, EuclideanTSPData.DistanceRounding.Midpoint) { Description = data.Description };
136            break;
137          case DistanceMeasure.UpperEuclidean:
138            ProbabilisticTSPData = new EuclideanPTSPData(data.Name, data.Coordinates, data.Probabilities, EuclideanTSPData.DistanceRounding.Ceiling) { Description = data.Description };
139            break;
140          case DistanceMeasure.Geo:
141            ProbabilisticTSPData = new GeoPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
142            break;
143          case DistanceMeasure.Manhattan:
144            ProbabilisticTSPData = new ManhattanPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
145            break;
146          case DistanceMeasure.Maximum:
147            ProbabilisticTSPData = new MaximumPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
148            break;
149          default:
150            throw new System.IO.InvalidDataException("An unknown distance measure is given in the instance!");
151        }
152      }
153      BestKnownSolution = null;
154      BestKnownQuality = double.NaN;
155
156      if (data.BestKnownTour != null) {
157        try {
158          var tour = new Permutation(PermutationTypes.RelativeUndirected, data.BestKnownTour);
159          var tourLength = Evaluate(tour, new MersenneTwister(1));
160          BestKnownSolution = new ProbabilisticTSPSolution(data.Coordinates != null ? new DoubleMatrix(data.Coordinates) : null, new PercentArray(data.Probabilities), tour, new DoubleValue(tourLength));
161          BestKnownQuality = tourLength;
162        } catch (InvalidOperationException) {
163          if (data.BestKnownQuality.HasValue)
164            BestKnownQuality = data.BestKnownQuality.Value;
165        }
166      } else if (data.BestKnownQuality.HasValue) {
167        BestKnownQuality = data.BestKnownQuality.Value;
168      }
169      OnReset();
170    }
171  }
172}
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