1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Encodings.PermutationEncoding;
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29 | using HeuristicLab.Optimization.Operators;
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30 | using HeuristicLab.Parameters;
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31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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32 |
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33 | namespace HeuristicLab.Problems.TravelingSalesman {
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34 | /// <summary>
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35 | /// An operator that relinks paths between traveling salesman solutions using a multiple guiding strategy.
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36 | /// </summary>
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37 | /// <remarks>
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38 | /// The operator incrementally changes the initiating solution towards the guiding solution by correcting edges as needed. For each city it choses the best edge from all guiding solutions.
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39 | /// </remarks>
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40 | [Item("TSPMultipleGuidesPathRelinker", "An operator that relinks paths between traveling salesman solutions using a multiple guiding strategy.")]
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41 | [StorableClass]
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42 | public sealed class TSPMultipleGuidesPathRelinker : SingleObjectivePathRelinker {
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43 | #region Parameter properties
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44 | public ILookupParameter<DistanceMatrix> DistanceMatrixParameter {
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45 | get { return (ILookupParameter<DistanceMatrix>)Parameters["DistanceMatrix"]; }
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46 | }
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47 | #endregion
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48 |
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49 | #region Properties
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50 | public DistanceMatrix DistanceMatrix {
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51 | get { return DistanceMatrixParameter.ActualValue; }
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52 | }
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53 | #endregion
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54 |
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55 | [StorableConstructor]
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56 | private TSPMultipleGuidesPathRelinker(bool deserializing) : base(deserializing) { }
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57 | private TSPMultipleGuidesPathRelinker(TSPMultipleGuidesPathRelinker original, Cloner cloner) : base(original, cloner) { }
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58 | public TSPMultipleGuidesPathRelinker()
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59 | : base() {
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60 | #region Create parameters
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61 | Parameters.Add(new LookupParameter<DistanceMatrix>("DistanceMatrix", "The matrix which contains the distances between the cities."));
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62 | #endregion
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63 | }
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64 |
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65 | public override IDeepCloneable Clone(Cloner cloner) {
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66 | return new TSPMultipleGuidesPathRelinker(this, cloner);
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67 | }
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68 |
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69 | public static ItemArray<IItem> Apply(IItem initiator, IItem[] guides, DistanceMatrix distances, PercentValue n) {
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70 | if (!(initiator is Permutation) || guides.Any(x => !(x is Permutation)))
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71 | throw new ArgumentException("Cannot relink path because some of the provided solutions have the wrong type.");
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72 | if (n.Value <= 0.0)
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73 | throw new ArgumentException("RelinkingAccuracy must be greater than 0.");
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74 |
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75 | Permutation v1 = initiator.Clone() as Permutation;
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76 | Permutation[] targets = new Permutation[guides.Length];
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77 | Array.Copy(guides, targets, guides.Length);
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78 |
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79 | if (targets.Any(x => x.Length != v1.Length))
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80 | throw new ArgumentException("At least one solution is of different length.");
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81 |
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82 | IList<Permutation> solutions = new List<Permutation>();
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83 | for (int i = 0; i < v1.Length; i++) {
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84 | int currCityIndex = i;
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85 | int bestCityIndex = (i + 1) % v1.Length;
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86 | double currDistance = distances[v1[currCityIndex], v1[bestCityIndex]];
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87 | targets.ToList().ForEach(solution => {
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88 | var node = solution.Select((x, index) => new { Id = x, Index = index }).First(x => x.Id == v1[currCityIndex]);
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89 | int pred = solution[(node.Index - 1 + solution.Length) % solution.Length];
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90 | int succ = solution[(node.Index + 1) % solution.Length];
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91 | var results = new[] { pred, succ }.Select(x => new { Id = x, Distance = distances[x, node.Id] });
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92 | if (results.Any(x => x.Distance < currDistance)) {
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93 | var bestCity = results.OrderBy(x => x.Distance).First();
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94 | bestCityIndex = v1.Select((x, index) => new { Id = x, Index = index }).First(x => x.Id == bestCity.Id).Index;
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95 | currDistance = bestCity.Distance;
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96 | }
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97 | });
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98 | Invert(v1, currCityIndex + 1, bestCityIndex);
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99 | solutions.Add(v1.Clone() as Permutation);
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100 | }
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101 |
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102 | IList<IItem> selection = new List<IItem>();
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103 | if (solutions.Count > 0) {
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104 | int noSol = (int)(solutions.Count * n.Value);
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105 | if (noSol <= 0) noSol++;
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106 | double stepSize = (double)solutions.Count / (double)noSol;
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107 | for (int i = 0; i < noSol; i++)
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108 | selection.Add(solutions.ElementAt((int)((i + 1) * stepSize - stepSize * 0.5)));
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109 | }
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110 |
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111 | return new ItemArray<IItem>(selection);
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112 | }
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113 |
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114 | private static void Invert(Permutation sol, int i, int j) {
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115 | if (i != j)
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116 | for (int a = 0; a < Math.Abs(i - j) / 2; a++)
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117 | if (sol[(i + a) % sol.Length] != sol[(j - a + sol.Length) % sol.Length]) {
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118 | // XOR swap
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119 | sol[(i + a) % sol.Length] ^= sol[(j - a + sol.Length) % sol.Length];
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120 | sol[(j - a + sol.Length) % sol.Length] ^= sol[(i + a) % sol.Length];
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121 | sol[(i + a) % sol.Length] ^= sol[(j - a + sol.Length) % sol.Length];
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122 | }
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123 | }
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124 |
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125 | protected override ItemArray<IItem> Relink(ItemArray<IItem> parents, PercentValue n) {
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126 | if (parents.Length < 2)
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127 | throw new ArgumentException("The number of parents is smaller than 2.");
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128 | return Apply(parents[0], parents.Skip(1).ToArray(), DistanceMatrix, n);
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129 | }
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130 | }
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131 | }
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