1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2010 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 HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Encodings.PermutationEncoding;
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27 | using HeuristicLab.Optimization;
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28 | using HeuristicLab.Parameters;
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29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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30 | using HeuristicLab.Common;
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31 | using HeuristicLab.Problems.VehicleRouting.Interfaces;
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32 | using HeuristicLab.Problems.VehicleRouting.ProblemInstances;
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33 | using HeuristicLab.Problems.VehicleRouting.Variants;
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34 | using HeuristicLab.Problems.VehicleRouting.Encodings.Potvin;
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35 | using HeuristicLab.Problems.VehicleRouting;
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36 |
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37 | namespace HeuristicLab.PDPSimulation.Operators {
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38 | [Item("DynPushForwardInsertionCreator", "Creates a randomly initialized VRP solution.")]
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39 | [StorableClass]
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40 | public sealed class DynPushForwardInsertionCreator : PotvinCreator, IStochasticOperator {
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41 | #region IStochasticOperator Members
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42 | public ILookupParameter<IRandom> RandomParameter {
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43 | get { return (LookupParameter<IRandom>)Parameters["Random"]; }
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44 | }
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45 | #endregion
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46 |
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47 | public IValueParameter<DoubleValue> Alpha {
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48 | get { return (IValueParameter<DoubleValue>)Parameters["Alpha"]; }
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49 | }
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50 | public IValueParameter<DoubleValue> AlphaVariance {
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51 | get { return (IValueParameter<DoubleValue>)Parameters["AlphaVariance"]; }
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52 | }
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53 | public IValueParameter<DoubleValue> Beta {
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54 | get { return (IValueParameter<DoubleValue>)Parameters["Beta"]; }
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55 | }
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56 | public IValueParameter<DoubleValue> BetaVariance {
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57 | get { return (IValueParameter<DoubleValue>)Parameters["BetaVariance"]; }
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58 | }
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59 | public IValueParameter<DoubleValue> Gamma {
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60 | get { return (IValueParameter<DoubleValue>)Parameters["Gamma"]; }
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61 | }
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62 | public IValueParameter<DoubleValue> GammaVariance {
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63 | get { return (IValueParameter<DoubleValue>)Parameters["GammaVariance"]; }
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64 | }
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65 |
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66 | [StorableConstructor]
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67 | private DynPushForwardInsertionCreator(bool deserializing) : base(deserializing) { }
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68 |
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69 | public DynPushForwardInsertionCreator()
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70 | : base() {
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71 | Parameters.Add(new LookupParameter<IRandom>("Random", "The pseudo random number generator."));
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72 | Parameters.Add(new ValueParameter<DoubleValue>("Alpha", "The alpha value.", new DoubleValue(0.7)));
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73 | Parameters.Add(new ValueParameter<DoubleValue>("AlphaVariance", "The alpha variance.", new DoubleValue(0.5)));
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74 | Parameters.Add(new ValueParameter<DoubleValue>("Beta", "The beta value.", new DoubleValue(0.1)));
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75 | Parameters.Add(new ValueParameter<DoubleValue>("BetaVariance", "The beta variance.", new DoubleValue(0.07)));
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76 | Parameters.Add(new ValueParameter<DoubleValue>("Gamma", "The gamma value.", new DoubleValue(0.2)));
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77 | Parameters.Add(new ValueParameter<DoubleValue>("GammaVariance", "The gamma variance.", new DoubleValue(0.14)));
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78 | }
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79 |
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80 | public override IDeepCloneable Clone(Cloner cloner) {
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81 | return new DynPushForwardInsertionCreator(this, cloner);
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82 | }
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83 |
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84 | private DynPushForwardInsertionCreator(DynPushForwardInsertionCreator original, Cloner cloner)
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85 | : base(original, cloner) {
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86 | }
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87 |
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88 | // use the Box-Mueller transform in the polar form to generate a N(0,1) random variable out of two uniformly distributed random variables
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89 | private static double Gauss(IRandom random) {
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90 | double u = 0.0, v = 0.0, s = 0.0;
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91 | do {
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92 | u = (random.NextDouble() * 2) - 1;
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93 | v = (random.NextDouble() * 2) - 1;
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94 | s = Math.Sqrt(u * u + v * v);
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95 | } while (s < Double.Epsilon || s > 1);
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96 | return u * Math.Sqrt((-2.0 * Math.Log(s)) / s);
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97 | }
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98 |
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99 | private static double N(double mu, double sigma, IRandom random) {
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100 | return mu + (sigma * Gauss(random)); // transform the random variable sampled from N(0,1) to N(mu,sigma)
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101 | }
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102 |
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103 | private static double GetDistance(int start, int end, IVRPProblemInstance problemInstance, PotvinEncoding solution) {
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104 | double distance = 0.0;
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105 |
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106 | if (problemInstance is DynPDPProblemInstance) {
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107 | distance = (problemInstance as DynPDPProblemInstance).GetDistance(start, end);
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108 | }
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109 | else if (problemInstance.UseDistanceMatrix.Value && problemInstance.DistanceMatrix != null) {
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110 | distance = problemInstance.DistanceMatrix[start, end];
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111 | } else {
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112 | double startX = problemInstance.Coordinates[start, 0];
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113 | double startY = problemInstance.Coordinates[start, 1];
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114 |
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115 | double endX = problemInstance.Coordinates[end, 0];
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116 | double endY = problemInstance.Coordinates[end, 1];
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117 |
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118 | distance =
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119 | Math.Sqrt(
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120 | Math.Pow(startX - endX, 2) +
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121 | Math.Pow(startY - endY, 2));
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122 | }
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123 |
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124 | return distance;
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125 | }
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126 |
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127 | private static double GetCosts(int customer, int vehicle, IVRPProblemInstance problemInstance,
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128 | Dictionary<int, List<int>> vehicles, Dictionary<int, Tour> vehicleTours, List<bool> vehicleUsed, PotvinEncoding solution,
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129 | double alpha, double beta, double gamma, out bool feasible, out bool existingRoute) {
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130 | int depotCount = 1;
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131 | IMultiDepotProblemInstance mdp = problemInstance as IMultiDepotProblemInstance;
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132 | if (mdp != null) {
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133 | depotCount = mdp.Depots.Value;
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134 | }
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135 |
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136 | feasible = true;
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137 |
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138 | double distance = GetDistance(vehicle, customer + depotCount - 1, problemInstance, solution);
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139 | if (vehicleUsed != null) {
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140 | existingRoute = vehicleUsed[vehicle];
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141 | } else {
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142 | existingRoute = true;
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143 | }
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144 |
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145 | double dueTime = 0;
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146 | if (problemInstance is ITimeWindowedProblemInstance) {
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147 | ITimeWindowedProblemInstance vrptw = problemInstance as ITimeWindowedProblemInstance;
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148 | dueTime = vrptw.DueTime[customer + depotCount - 1];
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149 | }
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150 |
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151 | if (vehicleTours.ContainsKey(vehicle)) {
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152 | Tour tour = vehicleTours[vehicle];
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153 |
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154 | IPickupAndDeliveryProblemInstance pdp = problemInstance as IPickupAndDeliveryProblemInstance;
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155 | if (pdp != null && pdp.GetPickupDeliveryLocation(customer) > 0) {
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156 | solution.InsertPair(tour, customer, pdp.GetPickupDeliveryLocation(customer), problemInstance);
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157 | } else {
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158 | tour.Stops.Insert(solution.FindBestInsertionPlace(tour, customer), customer);
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159 | }
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160 |
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161 | feasible = problemInstance.TourFeasible(tour, solution);
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162 |
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163 | tour.Stops.Remove(customer);
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164 | if (pdp != null && pdp.GetPickupDeliveryLocation(customer) > 0) {
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165 | tour.Stops.Remove(pdp.GetPickupDeliveryLocation(customer));
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166 | }
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167 | }
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168 | else if (problemInstance is ITimeWindowedProblemInstance) {
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169 | IPickupAndDeliveryProblemInstance pdp = problemInstance as IPickupAndDeliveryProblemInstance;
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170 | ITimeWindowedProblemInstance vrptw = problemInstance as ITimeWindowedProblemInstance;
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171 | double time = vrptw.ReadyTime[vehicle];
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172 | time += distance;
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173 | if (time > dueTime) {
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174 | feasible = false;
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175 | } else {
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176 | time += vrptw.ServiceTime[customer - 1];
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177 | if (pdp != null && pdp.GetPickupDeliveryLocation(customer) > 0) {
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178 | int targetCustomer = pdp.GetPickupDeliveryLocation(customer);
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179 | time += GetDistance(customer + depotCount - 1, targetCustomer + depotCount - 1, problemInstance, solution);
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180 | if (time > vrptw.DueTime[targetCustomer + depotCount - 1]) {
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181 | feasible = false;
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182 | }
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183 |
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184 | time += vrptw.ServiceTime[targetCustomer - 1];
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185 | time += GetDistance(targetCustomer + depotCount - 1, vehicle, problemInstance, solution);
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186 |
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187 | if (time > vrptw.DueTime[vehicle]) {
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188 | feasible = false;
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189 | }
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190 | } else {
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191 | time += GetDistance(customer + depotCount - 1, vehicle, problemInstance, solution);
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192 | if (time > vrptw.DueTime[vehicle]) {
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193 | feasible = false;
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194 | }
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195 | }
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196 | }
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197 | }
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198 |
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199 | if (problemInstance is IHeterogenousCapacitatedProblemInstance) {
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200 | IHeterogenousCapacitatedProblemInstance cvrp = problemInstance as IHeterogenousCapacitatedProblemInstance;
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201 | double demand = problemInstance.GetDemand(customer);
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202 | if (demand > cvrp.Capacity[vehicle])
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203 | feasible = false;
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204 | } else if (problemInstance is IHomogenousCapacitatedProblemInstance) {
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205 | IHomogenousCapacitatedProblemInstance cvrp = problemInstance as IHomogenousCapacitatedProblemInstance;
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206 | double demand = problemInstance.GetDemand(customer);
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207 | if (demand > cvrp.Capacity.Value)
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208 | feasible = false;
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209 | }
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210 |
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211 | double x0 = problemInstance.Coordinates[vehicle, 0];
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212 | double y0 = problemInstance.Coordinates[vehicle, 1];
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213 | double dist;
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214 | if (problemInstance.Coordinates[customer + depotCount - 1, 0] < x0)
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215 | dist = -distance;
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216 | else
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217 | dist = distance;
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218 | double polarAngle = (dist != 0 ? (Math.Asin((problemInstance.Coordinates[customer + depotCount - 1, 1] - y0) / dist) / 360 * dist) : 0);
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219 |
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220 | if (problemInstance is ITimeWindowedProblemInstance) {
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221 | ITimeWindowedProblemInstance vrptw = problemInstance as ITimeWindowedProblemInstance;
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222 |
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223 | if (dueTime == double.MaxValue)
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224 | dueTime = 0;
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225 | else {
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226 | dueTime -= vrptw.ReadyTime[vehicle];
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227 | }
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228 | }
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229 |
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230 | double cost = alpha * distance + // distance 0 <-> City[i]
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231 | -beta * dueTime + // latest arrival time
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232 | -gamma * polarAngle; // polar angle
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233 |
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234 | if (vehicleUsed != null) {
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235 | if (!vehicleUsed[vehicle])
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236 | cost += problemInstance.FleetUsageFactor.Value;
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237 | }
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238 |
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239 | return cost;
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240 | }
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241 |
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242 | private static int GetNearestDepot(IVRPProblemInstance problemInstance, List<int> depots, int customer,
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243 | Dictionary<int, List<int>> vehicles, Dictionary<int, Tour> vehicleTours, List<bool> vehicleUsed, PotvinEncoding solution,
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244 | double alpha, double beta, double gamma, out double minCost, out bool bound, out bool bestExistingRoute) {
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245 | int nearest = -1;
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246 | minCost = double.MaxValue;
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247 | bestExistingRoute = false;
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248 |
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249 | bool bestFeasible = false;
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250 | int feasibleCount = 0;
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251 | foreach (int depot in depots) {
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252 | int vehicle = vehicles[depot][0];
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253 |
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254 | bool existingRoute;
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255 | bool feasible;
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256 | double cost = GetCosts(
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257 | customer, vehicle,
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258 | problemInstance, vehicles, vehicleTours, vehicleUsed,
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259 | solution, alpha, beta, gamma, out feasible, out existingRoute);
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260 |
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261 | if (feasible)
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262 | feasibleCount++;
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263 |
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264 | if ((feasible && !bestFeasible) ||
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265 | (feasible == bestFeasible && existingRoute && !bestExistingRoute) ||
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266 | (feasible == bestFeasible && existingRoute == bestExistingRoute && cost < minCost)) {
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267 | minCost = cost;
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268 | nearest = depot;
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269 | bestFeasible = feasible;
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270 | bestExistingRoute = existingRoute;
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271 | }
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272 | }
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273 |
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274 | bound = (feasibleCount == 1);
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275 |
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276 | return nearest;
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277 | }
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278 |
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279 | private static List<int> SortCustomers(IVRPProblemInstance problemInstance, List<int> customers, List<int> depots,
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280 | Dictionary<int, int> depotAssignment, Dictionary<int, int> customerBinding,
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281 | Dictionary<int, List<int>> vehicles, Dictionary<int, Tour> vehicleTours, List<bool> vehicleUsed, PotvinEncoding solution,
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282 | double alpha, double beta, double gamma) {
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283 | List<int> sortedCustomers = new List<int>();
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284 | depotAssignment.Clear();
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285 | customerBinding.Clear();
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286 |
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287 | List<bool> boundList = new List<bool>();
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288 | List<bool> existingRouteList = new List<bool>();
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289 | List<double> costList = new List<double>();
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290 |
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291 | for (int i = 0; i < customers.Count; i++) {
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292 | double cost;
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293 | bool bound;
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294 | bool existingRoute;
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295 | int depot = GetNearestDepot(problemInstance, depots, customers[i], vehicles, vehicleTours, vehicleUsed, solution,
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296 | alpha, beta, gamma,
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297 | out cost, out bound, out existingRoute);
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298 | depotAssignment[customers[i]] = depot;
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299 | if (bound) {
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300 | customerBinding.Add(customers[i], depot);
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301 | }
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302 |
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303 | int index = 0;
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304 | while (index < costList.Count &&
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305 | ((!bound && boundList[index]) ||
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306 | (bound == boundList[index] && !existingRoute && existingRouteList[index]) ||
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307 | (bound == boundList[index] && existingRoute == existingRouteList[index] && costList[index] < cost)))
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308 | index++;
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309 |
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310 | costList.Insert(index, cost);
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311 | boundList.Insert(index, bound);
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312 | existingRouteList.Insert(index, existingRoute);
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313 | sortedCustomers.Insert(index, customers[i]);
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314 | }
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315 |
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316 | return sortedCustomers;
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317 | }
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318 |
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319 | private static bool RemoveUnusedDepots(List<int> depots, Dictionary<int, List<int>> vehicles) {
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320 | List<int> toBeRemoved = new List<int>();
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321 |
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322 | foreach (int depot in depots) {
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323 | if (vehicles[depot].Count == 0)
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324 | toBeRemoved.Add(depot);
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325 | }
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326 |
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327 | foreach (int depot in toBeRemoved) {
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328 | depots.Remove(depot);
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329 | vehicles.Remove(depot);
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330 | }
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331 |
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332 | return toBeRemoved.Count > 0;
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333 | }
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334 |
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335 | private static Dictionary<int, Tour> CreateInitialTours(IVRPProblemInstance problemInstance, Dictionary<int, List<int>> vehicles, PotvinEncoding result) {
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336 | Dictionary<int, Tour> vehicleTours = new Dictionary<int, Tour>();
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337 | IPickupAndDeliveryProblemInstance pdp = problemInstance as IPickupAndDeliveryProblemInstance;
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338 |
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339 | int currentVehicle;
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340 |
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341 | for (int i = 1; i <= problemInstance.Cities.Value; i++) {
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342 | if (pdp != null && pdp.GetPickupDeliveryLocation(i) <= 0) {
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343 | currentVehicle = -pdp.GetPickupDeliveryLocation(i);
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344 | foreach (int depot in vehicles.Keys) {
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345 | if (vehicles[depot].Contains(currentVehicle)) {
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346 | vehicles[depot].Remove(currentVehicle);
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347 | vehicles[depot].Insert(0, currentVehicle);
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348 | break;
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349 | }
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350 | }
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351 |
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352 | Tour tour;
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353 |
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354 | if (!vehicleTours.ContainsKey(currentVehicle)) {
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355 | tour = new Tour();
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356 | result.Tours.Add(tour);
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357 | vehicleTours[currentVehicle] = tour;
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358 | result.VehicleAssignment[result.Tours.Count - 1] = currentVehicle;
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359 | } else {
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360 | tour = vehicleTours[currentVehicle];
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361 | }
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362 |
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363 | tour.Stops.Add(i);
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364 | }
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365 | }
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366 |
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367 | foreach (int vehicle in vehicleTours.Keys) {
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368 | Tour vehicleTour = vehicleTours[vehicle];
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369 | List<int> customers = new List<int>(vehicleTour.Stops);
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370 | vehicleTour.Stops.Clear();
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371 |
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372 | if (problemInstance is DynPDPProblemInstance &&
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373 | (problemInstance as DynPDPProblemInstance).CurrentPlan != null) {
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374 | PotvinEncoding plan = (problemInstance as DynPDPProblemInstance).CurrentPlan;
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375 | Tour planTour = plan.Tours.Find(t => plan.GetVehicleAssignment(plan.Tours.IndexOf(t)) == vehicle);
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376 |
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377 | customers.Sort((x, y) => planTour.Stops.IndexOf(x).CompareTo(planTour.Stops.IndexOf(y)));
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378 | foreach (int customer in customers)
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379 | vehicleTour.Stops.Add(customer);
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380 | } else {
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381 | for (int i = 0; i < customers.Count; i++) {
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382 | int stop = result.FindBestInsertionPlace(vehicleTour, customers[i]);
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383 | vehicleTour.Stops.Insert(stop, customers[i]);
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384 | }
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385 | }
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386 | }
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387 |
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388 | return vehicleTours;
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389 | }
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390 |
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391 | public static PotvinEncoding CreateSolution(IVRPProblemInstance problemInstance, IRandom random, List<bool> vehicleUsed,
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392 | double alphaValue = 0.7, double betaValue = 0.1, double gammaValue = 0.2,
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393 | double alphaVariance = 0.5, double betaVariance = 0.07, double gammaVariance = 0.14) {
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394 | PotvinEncoding result = new PotvinEncoding(problemInstance);
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395 |
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396 | IPickupAndDeliveryProblemInstance pdp = problemInstance as IPickupAndDeliveryProblemInstance;
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397 | IMultiDepotProblemInstance mdp = problemInstance as IMultiDepotProblemInstance;
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398 |
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399 | if (mdp != null) {
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400 | for (int i = 0; i < result.VehicleAssignment.Length; i++) {
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401 | result.VehicleAssignment[i] = -1;
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402 | }
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403 | }
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404 |
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405 | double alpha, beta, gamma;
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406 | lock (random) {
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407 | alpha = N(alphaValue, Math.Sqrt(alphaVariance), random);
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408 | beta = N(betaValue, Math.Sqrt(betaVariance), random);
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409 | gamma = N(gammaValue, Math.Sqrt(gammaVariance), random);
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410 | }
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411 |
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412 | #region initialization
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413 | List<int> unroutedCustomers = new List<int>();
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414 | for (int i = 1; i <= problemInstance.Cities.Value; i++) {
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415 | if (pdp == null || (problemInstance.GetDemand(i) >= 0) || (pdp.GetPickupDeliveryLocation(i) == i))
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416 | unroutedCustomers.Add(i);
|
---|
417 | }
|
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418 |
|
---|
419 | List<int> depots = new List<int>();
|
---|
420 | if (mdp != null) {
|
---|
421 | for (int i = 0; i < mdp.Depots.Value; i++) {
|
---|
422 | depots.Add(i);
|
---|
423 | }
|
---|
424 | } else {
|
---|
425 | depots.Add(0);
|
---|
426 | }
|
---|
427 |
|
---|
428 | Dictionary<int, List<int>> vehicles = new Dictionary<int, List<int>>();
|
---|
429 | foreach (int depot in depots) {
|
---|
430 | vehicles[depot] = new List<int>();
|
---|
431 |
|
---|
432 | int vehicleCount = problemInstance.Vehicles.Value;
|
---|
433 | if (mdp != null) {
|
---|
434 | for (int vehicle = 0; vehicle < mdp.VehicleDepotAssignment.Length; vehicle++) {
|
---|
435 | if (mdp.VehicleDepotAssignment[vehicle] == depot) {
|
---|
436 | vehicles[depot].Add(vehicle);
|
---|
437 | }
|
---|
438 | }
|
---|
439 | } else {
|
---|
440 | for (int vehicle = 0; vehicle < vehicleCount; vehicle++) {
|
---|
441 | vehicles[depot].Add(vehicle);
|
---|
442 | }
|
---|
443 | }
|
---|
444 |
|
---|
445 | if (vehicleUsed != null) {
|
---|
446 | vehicles[depot].Sort(delegate(int x, int y) {
|
---|
447 | if (vehicleUsed[x] && vehicleUsed[y])
|
---|
448 | return 0;
|
---|
449 | else if (vehicleUsed[x])
|
---|
450 | return -1;
|
---|
451 | else
|
---|
452 | return 1;
|
---|
453 | });
|
---|
454 | }
|
---|
455 | }
|
---|
456 |
|
---|
457 | Dictionary<int, Tour> vehicleTours = CreateInitialTours(problemInstance, vehicles, result);
|
---|
458 | RemoveUnusedDepots(depots, vehicles);
|
---|
459 | #endregion
|
---|
460 |
|
---|
461 | #region route unrouted
|
---|
462 | if (unroutedCustomers.Count > 0) {
|
---|
463 | Tour tour;
|
---|
464 | int currentDepot;
|
---|
465 | int currentVehicle;
|
---|
466 | Dictionary<int, int> depotAssignment = new Dictionary<int, int>();
|
---|
467 |
|
---|
468 | //# sort customers globally - start new tour
|
---|
469 | Dictionary<int, int> customerBinding = new Dictionary<int, int>();
|
---|
470 | unroutedCustomers = SortCustomers(
|
---|
471 | problemInstance, unroutedCustomers, depots, depotAssignment, customerBinding,
|
---|
472 | vehicles, vehicleTours, vehicleUsed, result,
|
---|
473 | alpha, beta, gamma);
|
---|
474 |
|
---|
475 | int currentCustomer = unroutedCustomers[0];
|
---|
476 | currentDepot = depotAssignment[currentCustomer];
|
---|
477 | currentVehicle = vehicles[currentDepot][0];
|
---|
478 | vehicles[currentDepot].RemoveAt(0);
|
---|
479 | RemoveUnusedDepots(depots, vehicles);
|
---|
480 |
|
---|
481 | if (!vehicleTours.ContainsKey(currentVehicle)) {
|
---|
482 | tour = new Tour();
|
---|
483 | result.Tours.Add(tour);
|
---|
484 | result.VehicleAssignment[result.Tours.Count - 1] = currentVehicle;
|
---|
485 |
|
---|
486 | unroutedCustomers.Remove(currentCustomer);
|
---|
487 | tour.Stops.Add(currentCustomer);
|
---|
488 | if (pdp != null && pdp.GetPickupDeliveryLocation(currentCustomer) != currentCustomer) {
|
---|
489 | tour.Stops.Add(pdp.GetPickupDeliveryLocation(currentCustomer));
|
---|
490 | }
|
---|
491 | } else {
|
---|
492 | tour = vehicleTours[currentVehicle];
|
---|
493 | }
|
---|
494 |
|
---|
495 | while (unroutedCustomers.Count > 0) {
|
---|
496 | double minimumCost = double.MaxValue;
|
---|
497 | bool bestBoundToRoute = false;
|
---|
498 | int customer = -1;
|
---|
499 | int indexOfMinimumCost = -1;
|
---|
500 | int indexOfMinimumCost2 = -1;
|
---|
501 |
|
---|
502 | foreach (int unrouted in unroutedCustomers) {
|
---|
503 | bool boundToRoute = customerBinding.ContainsKey(unrouted) && customerBinding[unrouted] == currentDepot;
|
---|
504 |
|
---|
505 | VRPEvaluation eval = problemInstance.EvaluateTour(tour, result);
|
---|
506 | double originalCosts = eval.Quality;
|
---|
507 |
|
---|
508 | for (int i = 0; i <= tour.Stops.Count; i++) {
|
---|
509 | tour.Stops.Insert(i, unrouted);
|
---|
510 | eval = problemInstance.EvaluateTour(tour, result);
|
---|
511 | double tourCost = eval.Quality - originalCosts;
|
---|
512 |
|
---|
513 | if (pdp != null && pdp.GetPickupDeliveryLocation(unrouted) != unrouted) {
|
---|
514 | for (int j = i + 1; j <= tour.Stops.Count; j++) {
|
---|
515 | bool feasible;
|
---|
516 | double cost = tourCost +
|
---|
517 | problemInstance.GetInsertionCosts(eval, result, pdp.GetPickupDeliveryLocation(unrouted), 0, j, out feasible);
|
---|
518 | if ((cost < minimumCost || (!bestBoundToRoute && boundToRoute)) && (boundToRoute || !bestBoundToRoute) && feasible) {
|
---|
519 | customer = unrouted;
|
---|
520 | minimumCost = cost;
|
---|
521 | indexOfMinimumCost = i;
|
---|
522 | indexOfMinimumCost2 = j;
|
---|
523 | bestBoundToRoute = boundToRoute;
|
---|
524 | }
|
---|
525 | }
|
---|
526 | } else {
|
---|
527 | double cost = tourCost;
|
---|
528 | bool feasible = problemInstance.Feasible(eval);
|
---|
529 | if ((cost < minimumCost || (!bestBoundToRoute && boundToRoute)) && (boundToRoute || !bestBoundToRoute) && feasible) {
|
---|
530 | customer = unrouted;
|
---|
531 | minimumCost = cost;
|
---|
532 | indexOfMinimumCost = i;
|
---|
533 | bestBoundToRoute = boundToRoute;
|
---|
534 | }
|
---|
535 | }
|
---|
536 |
|
---|
537 | tour.Stops.RemoveAt(i);
|
---|
538 | }
|
---|
539 | }
|
---|
540 |
|
---|
541 | if (indexOfMinimumCost == -1 && vehicles.Count == 0) {
|
---|
542 | indexOfMinimumCost = tour.Stops.Count;
|
---|
543 | indexOfMinimumCost2 = tour.Stops.Count + 1;
|
---|
544 | customer = unroutedCustomers[0];
|
---|
545 | }
|
---|
546 |
|
---|
547 | // insert customer if found
|
---|
548 | if (indexOfMinimumCost != -1) {
|
---|
549 | tour.Stops.Insert(indexOfMinimumCost, customer);
|
---|
550 | if (pdp != null && pdp.GetPickupDeliveryLocation(customer) != customer) {
|
---|
551 | tour.Stops.Insert(indexOfMinimumCost2, pdp.GetPickupDeliveryLocation(customer));
|
---|
552 | }
|
---|
553 | unroutedCustomers.Remove(customer);
|
---|
554 | } else { // no feasible customer found
|
---|
555 | //# sort customers globally - start new tour
|
---|
556 | unroutedCustomers = SortCustomers(
|
---|
557 | problemInstance, unroutedCustomers, depots, depotAssignment, customerBinding,
|
---|
558 | vehicles, vehicleTours, vehicleUsed, result,
|
---|
559 | alpha, beta, gamma);
|
---|
560 |
|
---|
561 | currentCustomer = unroutedCustomers[0];
|
---|
562 | currentDepot = depotAssignment[currentCustomer];
|
---|
563 | currentVehicle = vehicles[currentDepot][0];
|
---|
564 | vehicles[currentDepot].RemoveAt(0);
|
---|
565 | RemoveUnusedDepots(depots, vehicles);
|
---|
566 |
|
---|
567 | if (!vehicleTours.ContainsKey(currentVehicle)) {
|
---|
568 | tour = new Tour();
|
---|
569 | result.Tours.Add(tour);
|
---|
570 | result.VehicleAssignment[result.Tours.Count - 1] = currentVehicle;
|
---|
571 |
|
---|
572 | unroutedCustomers.Remove(currentCustomer);
|
---|
573 | tour.Stops.Add(currentCustomer);
|
---|
574 | if (pdp != null && pdp.GetPickupDeliveryLocation(currentCustomer) != currentCustomer) {
|
---|
575 | tour.Stops.Add(pdp.GetPickupDeliveryLocation(currentCustomer));
|
---|
576 | }
|
---|
577 | } else {
|
---|
578 | tour = vehicleTours[currentVehicle];
|
---|
579 | }
|
---|
580 | }
|
---|
581 | }
|
---|
582 | }
|
---|
583 | #endregion
|
---|
584 |
|
---|
585 | #region assign vehicles
|
---|
586 | if (mdp != null) {
|
---|
587 | List<int> availableVehicles = new List<int>();
|
---|
588 | for (int i = 0; i < mdp.Vehicles.Value; i++)
|
---|
589 | availableVehicles.Add(i);
|
---|
590 |
|
---|
591 | for (int i = 0; i < result.VehicleAssignment.Length; i++) {
|
---|
592 | if (result.VehicleAssignment[i] != -1)
|
---|
593 | availableVehicles.Remove(result.VehicleAssignment[i]);
|
---|
594 | }
|
---|
595 |
|
---|
596 | for (int i = 0; i < result.VehicleAssignment.Length; i++) {
|
---|
597 | if (result.VehicleAssignment[i] == -1) {
|
---|
598 | result.VehicleAssignment[i] = availableVehicles[0];
|
---|
599 | availableVehicles.RemoveAt(0);
|
---|
600 | }
|
---|
601 | }
|
---|
602 | }
|
---|
603 | #endregion
|
---|
604 |
|
---|
605 | return result;
|
---|
606 | }
|
---|
607 |
|
---|
608 | public override IOperation Apply() {
|
---|
609 | List<bool> vehicleUsed = null;
|
---|
610 |
|
---|
611 | DynPDPProblemInstance instance = ProblemInstance as DynPDPProblemInstance;
|
---|
612 | if(instance != null) {
|
---|
613 | vehicleUsed = new List<bool>();
|
---|
614 | for (int i = 0; i < instance.VehicleUsed.Length; i++) {
|
---|
615 | vehicleUsed.Add(instance.VehicleUsed[i]);
|
---|
616 | }
|
---|
617 | }
|
---|
618 |
|
---|
619 | VRPToursParameter.ActualValue = CreateSolution(ProblemInstance, RandomParameter.ActualValue, vehicleUsed,
|
---|
620 | Alpha.Value.Value, Beta.Value.Value, Gamma.Value.Value,
|
---|
621 | AlphaVariance.Value.Value, BetaVariance.Value.Value, GammaVariance.Value.Value);
|
---|
622 |
|
---|
623 | return base.Apply();
|
---|
624 | }
|
---|
625 | }
|
---|
626 | }
|
---|
627 |
|
---|