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source: branches/PTSP/HeuristicLab.Problems.PTSP/3.3/PTSP.cs @ 12249

Last change on this file since 12249 was 12228, checked in by apolidur, 10 years ago

#2221: Local improvement operator for VNS

File size: 7.1 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.Collections.Generic;
24using System.Linq;
25using System.Text;
26using System.Threading.Tasks;
27using HeuristicLab.Optimization;
28using HeuristicLab.PluginInfrastructure;
29using HeuristicLab.Core;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31using HeuristicLab.Problems.Instances;
32using HeuristicLab.Encodings.PermutationEncoding;
33using HeuristicLab.Common;
34using HeuristicLab.Parameters;
35using HeuristicLab.Data;
36
37namespace HeuristicLab.Problems.PTSP {
38  [Item("Probabilistic Traveling Salesman Problem", "Represents a Probabilistic Traveling Salesman Problem.")]
39  [StorableClass]
40  public abstract class ProbabilisticTravelingSalesmanProblem : SingleObjectiveBasicProblem<PermutationEncoding>, IStorableContent,
41  IProblemInstanceConsumer<TSPData> {
42    private static readonly int DistanceMatrixSizeLimit = 1000;
43
44    #region Parameter Properties
45    public OptionalValueParameter<DoubleMatrix> CoordinatesParameter {
46      get { return (OptionalValueParameter<DoubleMatrix>)Parameters["Coordinates"]; }
47    }
48    public OptionalValueParameter<DistanceMatrix> DistanceMatrixParameter {
49      get { return (OptionalValueParameter<DistanceMatrix>)Parameters["DistanceMatrix"]; }
50    }
51    public ValueParameter<BoolValue> UseDistanceMatrixParameter {
52      get { return (ValueParameter<BoolValue>)Parameters["UseDistanceMatrix"]; }
53    }
54    public OptionalValueParameter<Permutation> BestKnownSolutionParameter {
55      get { return (OptionalValueParameter<Permutation>)Parameters["BestKnownSolution"]; }
56    }
57    public ValueParameter<DoubleArray> ProbabilityMatrixParameter {
58      get { return (ValueParameter<DoubleArray>)Parameters["ProbabilityMatrix"]; }
59    }
60    public ValueParameter<IntValue> SampleSizeParameter {
61      get { return (ValueParameter<IntValue>)Parameters["SampleSize"]; }
62    }
63
64    #endregion
65
66    #region Properties
67    public DoubleMatrix Coordinates {
68      get { return CoordinatesParameter.Value; }
69      set { CoordinatesParameter.Value = value; }
70    }
71    public DistanceMatrix DistanceMatrix {
72      get { return DistanceMatrixParameter.Value; }
73      set { DistanceMatrixParameter.Value = value; }
74    }
75    public BoolValue UseDistanceMatrix {
76      get { return UseDistanceMatrixParameter.Value; }
77      set { UseDistanceMatrixParameter.Value = value; }
78    }
79    public Permutation BestKnownSolution {
80      get { return BestKnownSolutionParameter.Value; }
81      set { BestKnownSolutionParameter.Value = value; }
82    }
83    public DoubleArray ProbabilityMatrix {
84      get { return ProbabilityMatrixParameter.Value; }
85      set { ProbabilityMatrixParameter.Value = value; }
86    }
87    public IntValue SampleSize {
88      get { return SampleSizeParameter.Value; }
89      set { SampleSizeParameter.Value = value; }
90    }
91    #endregion
92   
93
94    public override bool Maximization {
95      get { return false; }
96    }
97
98    [StorableConstructor]
99    protected ProbabilisticTravelingSalesmanProblem(bool deserializing) : base(deserializing) { }
100    protected ProbabilisticTravelingSalesmanProblem(ProbabilisticTravelingSalesmanProblem original, Cloner cloner)
101      : base(original, cloner) {
102    }
103
104    public ProbabilisticTravelingSalesmanProblem() {
105      Parameters.Add(new OptionalValueParameter<DoubleMatrix>("Coordinates", "The x- and y-Coordinates of the cities."));
106      Parameters.Add(new OptionalValueParameter<DistanceMatrix>("DistanceMatrix", "The matrix which contains the distances between the cities."));
107      Parameters.Add(new ValueParameter<BoolValue>("UseDistanceMatrix", "True if the coordinates based evaluators should calculate the distance matrix from the coordinates and use it for evaluation similar to the distance matrix evaluator, otherwise false.", new BoolValue(true)));
108      Parameters.Add(new OptionalValueParameter<Permutation>("BestKnownSolution", "The best known solution of this TSP instance."));
109      Parameters.Add(new ValueParameter<DoubleArray>("ProbabilityMatrix", "The matrix which contains the probabilities of each of the cities."));
110
111      Coordinates = new DoubleMatrix(new double[,] {
112        { 100, 100 }, { 100, 200 }, { 100, 300 }, { 100, 400 },
113        { 200, 100 }, { 200, 200 }, { 200, 300 }, { 200, 400 },
114        { 300, 100 }, { 300, 200 }, { 300, 300 }, { 300, 400 },
115        { 400, 100 }, { 400, 200 }, { 400, 300 }, { 400, 400 }
116      });
117
118      ProbabilityMatrix = new DoubleArray(new double[] {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1});
119     
120    }
121
122    public virtual void Load(TSPData data) {
123      if (data.Coordinates == null && data.Distances == null)
124        throw new System.IO.InvalidDataException("The given instance specifies neither coordinates nor distances!");
125      if (data.Dimension > DistanceMatrixSizeLimit && (data.DistanceMeasure == DistanceMeasure.Att
126        || data.DistanceMeasure == DistanceMeasure.Manhattan
127        || data.DistanceMeasure == DistanceMeasure.Maximum))
128        throw new System.IO.InvalidDataException("The given instance uses an unsupported distance measure and is too large for using a distance matrix.");
129      if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2)
130        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.");
131
132      Name = data.Name;
133      Description = data.Description;
134
135      bool clearCoordinates = false, clearDistanceMatrix = false;
136      if (data.Coordinates != null && data.Coordinates.GetLength(0) > 0)
137        Coordinates = new DoubleMatrix(data.Coordinates);
138      else clearCoordinates = true;
139
140      // reset them after assigning the evaluator
141      if (clearCoordinates) Coordinates = null;
142      if (clearDistanceMatrix) DistanceMatrix = null;
143
144      DistanceMatrix = new DistanceMatrix(data.GetDistanceMatrix());
145      // Get Probabilities of cities using random with seed from hash function on the Name of the instance
146      ProbabilityMatrix = new DoubleArray(data.Dimension);
147      Random r = new Random(data.Name.GetHashCode());
148      for (int i = 0; i < data.Dimension; i++) {
149        ProbabilityMatrix[i] = r.NextDouble();
150      }
151      Encoding.Length = data.Dimension;
152
153      OnReset();
154    }
155  }
156}
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