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source: trunk/sources/HeuristicLab.Problems.Instances/3.3/Types/TSPData.cs @ 7846

Last change on this file since 7846 was 7548, checked in by abeham, 12 years ago

#1614: changed according to architects review

File size: 6.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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;
23
24namespace HeuristicLab.Problems.Instances {
25  public enum TSPDistanceMeasure { Direct, Euclidean, RoundedEuclidean, UpperEuclidean, Geo, Manhattan, Maximum, Att };
26
27  /// <summary>
28  /// Describes instances of the Traveling Salesman Problem (TSP).
29  /// </summary>
30  public class TSPData {
31    /// <summary>
32    /// The name of the instance
33    /// </summary>
34    public string Name { get; set; }
35    /// <summary>
36    /// Optional! The description of the instance
37    /// </summary>
38    public string Description { get; set; }
39
40    /// <summary>
41    /// The number of cities.
42    /// </summary>
43    public int Dimension { get; set; }
44    /// <summary>
45    /// Specifies the distance measure that is to be used.
46    /// </summary>
47    public TSPDistanceMeasure DistanceMeasure { get; set; }
48    /// <summary>
49    /// Optional! The distances are given in form of a distance matrix.
50    /// </summary>
51    /// <remarks>
52    /// Either this property or <see cref="Coordinates"/> needs to be specified.
53    /// </remarks>
54    public double[,] Distances { get; set; }
55    /// <summary>
56    /// Optional! A a matrix of dimension [N, 2] matrix where each row is one of the cities
57    /// and the colmns represent x and y coordinates respectively.
58    /// </summary>
59    /// <remarks>
60    /// Either this property or <see cref="Distances"/> needs to be specified.
61    ///
62    /// If no distance matrix is given, the distances have to be calculated by the
63    /// specified distance measure. If a distance matrix is given in addtion to the
64    /// coordinates, the distance matrix takes precedence and the coordinates are
65    /// for display only.
66    /// </remarks>
67    public double[,] Coordinates { get; set; }
68
69    /// <summary>
70    /// Optional! The best-known tour in path-encoding.
71    /// </summary>
72    public int[] BestKnownTour { get; set; }
73    /// <summary>
74    /// Optional! The quality of the best-known tour.
75    /// </summary>
76    public double? BestKnownQuality { get; set; }
77
78    /// <summary>
79    /// If only the coordinates are given, can calculate the distance matrix.
80    /// </summary>
81    /// <returns>A full distance matrix between all cities.</returns>
82    public double[,] GetDistanceMatrix() {
83      if (Distances != null) return Distances;
84      Distances = new double[Dimension, Dimension];
85      for (int i = 0; i < Dimension - 1; i++)
86        for (int j = i + 1; j < Dimension; j++) {
87          Distances[i, j] = GetDistance(i, j);
88          Distances[j, i] = Distances[i, j];
89        }
90      return Distances;
91    }
92
93    #region Private Helpers
94    private double GetDistance(int i, int j) {
95      switch (DistanceMeasure) {
96        case TSPDistanceMeasure.Att:
97          return AttDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]);
98        case TSPDistanceMeasure.Direct:
99          return Distances[i, j];
100        case TSPDistanceMeasure.Euclidean:
101          return EuclideanDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]);
102        case TSPDistanceMeasure.Geo:
103          return GeoDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]);
104        case TSPDistanceMeasure.Manhattan:
105          return ManhattanDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]);
106        case TSPDistanceMeasure.Maximum:
107          return MaximumDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]);
108        case TSPDistanceMeasure.RoundedEuclidean:
109          return Math.Round(EuclideanDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]));
110        case TSPDistanceMeasure.UpperEuclidean:
111          return Math.Ceiling(EuclideanDistance(Coordinates[i, 0], Coordinates[i, 1], Coordinates[j, 0], Coordinates[j, 1]));
112        default:
113          throw new InvalidOperationException("Distance measure is not known.");
114      }
115    }
116
117    private double AttDistance(double x1, double y1, double x2, double y2) {
118      return Math.Ceiling(Math.Sqrt(((x1 - x2) * (x1 - x2) + (y1 - y2) * (y1 - y2)) / 10.0));
119    }
120
121    private double EuclideanDistance(double x1, double y1, double x2, double y2) {
122      return Math.Sqrt((x1 - x2) * (x1 - x2) + (y1 - y2) * (y1 - y2));
123    }
124
125    private const double PI = 3.141592;
126    private const double RADIUS = 6378.388;
127    private double GeoDistance(double x1, double y1, double x2, double y2) {
128      double latitude1, longitude1, latitude2, longitude2;
129      double q1, q2, q3;
130      double length;
131
132      latitude1 = ConvertToRadian(x1);
133      longitude1 = ConvertToRadian(y1);
134      latitude2 = ConvertToRadian(x2);
135      longitude2 = ConvertToRadian(y2);
136
137      q1 = Math.Cos(longitude1 - longitude2);
138      q2 = Math.Cos(latitude1 - latitude2);
139      q3 = Math.Cos(latitude1 + latitude2);
140
141      length = (int)(RADIUS * Math.Acos(0.5 * ((1.0 + q1) * q2 - (1.0 - q1) * q3)) + 1.0);
142      return (length);
143    }
144
145    private double ConvertToRadian(double x) {
146      return PI * (Math.Truncate(x) + 5.0 * (x - Math.Truncate(x)) / 3.0) / 180.0;
147    }
148
149    private double ManhattanDistance(double x1, double y1, double x2, double y2) {
150      return Math.Round(Math.Abs(x1 - x2) + Math.Abs(y1 - y2), MidpointRounding.AwayFromZero);
151    }
152
153    private double MaximumDistance(double x1, double y1, double x2, double y2) {
154      return Math.Max(Math.Round(Math.Abs(x1 - x2), MidpointRounding.AwayFromZero), Math.Round(Math.Abs(y1 - y2), MidpointRounding.AwayFromZero));
155    }
156    #endregion
157  }
158}
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