[6608] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11171] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[6608] | 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 HeuristicLab.Common;
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| 23 | using HeuristicLab.Core;
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| 24 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 25 | using System.Collections.Generic;
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| 26 | using HeuristicLab.Data;
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| 27 | using System;
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| 28 | using HeuristicLab.Parameters;
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[6710] | 29 | using HeuristicLab.Problems.VehicleRouting.ProblemInstances;
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[6851] | 30 | using HeuristicLab.Problems.VehicleRouting.Interfaces;
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[6608] | 31 |
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| 32 | namespace HeuristicLab.Problems.VehicleRouting.Encodings.Potvin {
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| 33 | [Item("PotvinInsertionBasedCrossover", "The IBX crossover for VRP representations. It is implemented as described in Berger, J and Solois, M and Begin, R (1998). A hybrid genetic algorithm for the vehicle routing problem with time windows. LNCS 1418. Springer, London 114-127.")]
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| 34 | [StorableClass]
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| 35 | public sealed class PotvinInsertionBasedCrossover : PotvinCrossover {
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| 36 | public IValueParameter<IntValue> Length {
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| 37 | get { return (IValueParameter<IntValue>)Parameters["Length"]; }
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| 38 | }
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| 39 |
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| 40 | [StorableConstructor]
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| 41 | private PotvinInsertionBasedCrossover(bool deserializing) : base(deserializing) { }
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| 42 | private PotvinInsertionBasedCrossover(PotvinInsertionBasedCrossover original, Cloner cloner)
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| 43 | : base(original, cloner) {
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| 44 | }
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| 45 | public override IDeepCloneable Clone(Cloner cloner) {
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| 46 | return new PotvinInsertionBasedCrossover(this, cloner);
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| 47 | }
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| 48 | public PotvinInsertionBasedCrossover()
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| 49 | : base() {
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| 50 | Parameters.Add(new ValueParameter<IntValue>("Length", "The maximum length of the replaced route.", new IntValue(1)));
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| 51 | }
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| 52 |
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| 53 | private static int SelectRandomTourBiasedByLength(IRandom random, PotvinEncoding individual) {
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| 54 | int tourIndex = -1;
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| 55 |
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| 56 | double sum = 0.0;
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| 57 | double[] probabilities = new double[individual.Tours.Count];
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| 58 | for (int i = 0; i < individual.Tours.Count; i++) {
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| 59 | probabilities[i] = 1.0 / ((double)individual.Tours[i].Stops.Count / (double)individual.Cities);
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| 60 | sum += probabilities[i];
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| 61 | }
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| 62 |
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| 63 | double rand = random.NextDouble() * sum;
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| 64 | double cumulatedProbabilities = 0.0;
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| 65 | int index = 0;
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| 66 | while (tourIndex == -1 && index < probabilities.Length) {
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| 67 | if (cumulatedProbabilities <= rand && rand <= cumulatedProbabilities + probabilities[index])
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| 68 | tourIndex = index;
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| 69 |
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| 70 | cumulatedProbabilities += probabilities[index];
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| 71 | index++;
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| 72 | }
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| 73 |
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| 74 | return tourIndex;
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| 75 | }
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| 76 |
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[6851] | 77 | private double CalculateCentroidDistance(Tour t1, Tour t2, IVRPProblemInstance instance) {
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[6608] | 78 | double xSum = 0;
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| 79 | double ySum = 0;
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| 80 | double c1X, c1Y, c2X, c2Y;
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| 81 |
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| 82 | for (int i = 0; i < t1.Stops.Count; i++) {
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[6851] | 83 | xSum += instance.GetCoordinates(t1.Stops[i])[0];
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| 84 | ySum += instance.GetCoordinates(t1.Stops[i])[1];
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[6608] | 85 | }
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| 86 | c1X = xSum / t1.Stops.Count;
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| 87 | c1Y = ySum / t1.Stops.Count;
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| 88 |
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| 89 | for (int i = 0; i < t2.Stops.Count; i++) {
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[6851] | 90 | xSum += instance.GetCoordinates(t2.Stops[i])[0];
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| 91 | ySum += instance.GetCoordinates(t2.Stops[i])[1];
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[6608] | 92 | }
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| 93 | c2X = xSum / t1.Stops.Count;
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| 94 | c2Y = ySum / t1.Stops.Count;
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| 95 |
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| 96 | return Math.Sqrt(
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| 97 | (c1X - c2X) * (c1X - c2X) +
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| 98 | (c1Y - c2Y) * (c1Y - c2Y));
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| 99 | }
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| 100 |
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[6851] | 101 | private double CalculateMeanCentroidDistance(Tour t1, IList<Tour> tours, IVRPProblemInstance instance) {
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[6608] | 102 | double sum = 0;
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| 103 |
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| 104 | for (int i = 0; i < tours.Count; i++) {
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[6851] | 105 | sum += CalculateCentroidDistance(t1, tours[i], instance);
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[6608] | 106 | }
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| 107 |
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| 108 | return sum / tours.Count;
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| 109 | }
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| 110 |
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[6851] | 111 | private int SelectCityBiasedByNeighborDistance(IRandom random, Tour tour, IVRPEncoding solution) {
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[6608] | 112 | int cityIndex = -1;
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| 113 |
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| 114 | double sum = 0.0;
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| 115 | double[] probabilities = new double[tour.Stops.Count];
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| 116 | for (int i = 0; i < tour.Stops.Count; i++) {
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| 117 | int next;
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| 118 | if (i + 1 >= tour.Stops.Count)
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| 119 | next = 0;
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| 120 | else
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| 121 | next = tour.Stops[i + 1];
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| 122 | double distance = ProblemInstance.GetDistance(
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[6851] | 123 | tour.Stops[i], next, solution);
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[6608] | 124 |
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| 125 | int prev;
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| 126 | if (i - 1 < 0)
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| 127 | prev = 0;
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| 128 | else
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| 129 | prev = tour.Stops[i - 1];
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| 130 | distance += ProblemInstance.GetDistance(
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[6851] | 131 | tour.Stops[i], prev, solution);
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[6608] | 132 |
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| 133 | probabilities[i] = distance;
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| 134 | sum += probabilities[i];
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| 135 | }
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| 136 |
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| 137 | double rand = random.NextDouble() * sum;
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| 138 | double cumulatedProbabilities = 0.0;
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| 139 | int index = 0;
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| 140 | while (cityIndex == -1 && index < probabilities.Length) {
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| 141 | if (cumulatedProbabilities <= rand && rand <= cumulatedProbabilities + probabilities[index])
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| 142 | cityIndex = index;
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| 143 |
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| 144 | cumulatedProbabilities += probabilities[index];
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| 145 | index++;
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| 146 | }
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| 147 |
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| 148 | return cityIndex;
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| 149 | }
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| 150 |
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| 151 | private bool FindRouteInsertionPlace(
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[6838] | 152 | PotvinEncoding individual,
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[6608] | 153 | Tour tour,
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| 154 | int city, bool allowInfeasible, out int place) {
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| 155 | place = -1;
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[6710] | 156 |
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| 157 | if (tour.Stops.Contains(city))
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| 158 | return false;
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| 159 |
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[6752] | 160 | if (tour.Stops.Count == 0) {
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| 161 | place = 0;
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| 162 | return true;
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| 163 | }
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| 164 |
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[6608] | 165 | double minDetour = 0;
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[6838] | 166 | VRPEvaluation eval = ProblemInstance.EvaluateTour(tour, individual);
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[6752] | 167 | bool originalFeasible = ProblemInstance.Feasible(eval);
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[6608] | 168 |
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| 169 | for (int i = 0; i <= tour.Stops.Count; i++) {
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[6752] | 170 | bool feasible;
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[6851] | 171 | double detour = ProblemInstance.GetInsertionCosts(eval, individual, city, 0, i, out feasible);
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[6752] | 172 | if (feasible || allowInfeasible) {
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| 173 | if (place < 0 || detour < minDetour) {
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[6608] | 174 | place = i;
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| 175 | minDetour = detour;
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| 176 | }
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| 177 | }
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| 178 | }
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| 179 |
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| 180 | return place >= 0;
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| 181 | }
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| 182 |
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| 183 | private ICollection<int> GetUnrouted(PotvinEncoding solution, int cities) {
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| 184 | HashSet<int> undiscovered = new HashSet<int>();
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| 185 | for (int i = 1; i <= cities; i++) {
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| 186 | undiscovered.Add(i);
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| 187 | }
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| 188 |
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| 189 | foreach (Tour tour in solution.Tours) {
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| 190 | foreach (int city in tour.Stops)
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| 191 | undiscovered.Remove(city);
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| 192 | }
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| 193 |
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| 194 | return undiscovered;
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| 195 | }
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| 196 |
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| 197 | protected override PotvinEncoding Crossover(IRandom random, PotvinEncoding parent1, PotvinEncoding parent2) {
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[6851] | 198 | PotvinEncoding child = parent1.Clone() as PotvinEncoding;
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| 199 | child.Tours.Clear();
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[6608] | 200 |
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| 201 | bool allowInfeasible = AllowInfeasibleSolutions.Value.Value;
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| 202 |
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| 203 | List<Tour> R1 = new List<Tour>();
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| 204 | PotvinEncoding p1Clone = parent1.Clone() as PotvinEncoding;
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| 205 |
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| 206 | int length = Math.Min(Length.Value.Value, parent1.Tours.Count) + 1;
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[6947] | 207 | int k = 1;
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| 208 | if(length > 1)
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| 209 | k = random.Next(1, length);
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[6608] | 210 | for (int i = 0; i < k; i++) {
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| 211 | int index = SelectRandomTourBiasedByLength(random, p1Clone);
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| 212 | R1.Add(p1Clone.Tours[index]);
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| 213 | p1Clone.Tours.RemoveAt(index);
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| 214 | }
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| 215 |
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| 216 | foreach (Tour r1 in R1) {
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| 217 | List<int> R2 = new List<int>();
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| 218 |
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[6851] | 219 | double r = CalculateMeanCentroidDistance(r1, parent2.Tours, ProblemInstance);
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[6608] | 220 | foreach (Tour tour in parent2.Tours) {
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[6851] | 221 | if (CalculateCentroidDistance(r1, tour, ProblemInstance) <= r) {
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[6608] | 222 | R2.AddRange(tour.Stops);
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| 223 | }
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| 224 | }
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| 225 |
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| 226 | Tour childTour = new Tour();
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[6838] | 227 | child.Tours.Add(childTour);
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[6608] | 228 | childTour.Stops.AddRange(r1.Stops);
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| 229 |
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| 230 | //DESTROY - remove cities from r1
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[6947] | 231 | int removed = 1;
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| 232 | if(r1.Stops.Count > 1)
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| 233 | removed = random.Next(1, r1.Stops.Count + 1);
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[6608] | 234 | for (int i = 0; i < removed; i++) {
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[6851] | 235 | childTour.Stops.RemoveAt(SelectCityBiasedByNeighborDistance(random, childTour, child));
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[6608] | 236 | }
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| 237 |
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| 238 | //REPAIR - add cities from R2
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[6851] | 239 | int maxCount = 1;
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| 240 | if(R2.Count > 1)
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| 241 | maxCount = random.Next(1, Math.Min(5, R2.Count));
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[6608] | 242 | int count = 0;
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| 243 |
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| 244 | while (count < maxCount && R2.Count != 0) {
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| 245 | int index = random.Next(R2.Count);
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| 246 | int city = R2[index];
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| 247 | R2.RemoveAt(index);
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| 248 |
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| 249 | int place = -1;
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[6838] | 250 | bool found = FindRouteInsertionPlace(child, childTour, city, allowInfeasible, out place);
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[6752] | 251 | if (found) {
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[6608] | 252 | childTour.Stops.Insert(place, city);
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| 253 |
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| 254 | if (!Repair(random, child, childTour, ProblemInstance, allowInfeasible)) {
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| 255 | childTour.Stops.RemoveAt(place);
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| 256 | } else {
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| 257 | count++;
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| 258 | }
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| 259 | }
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| 260 | }
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| 261 |
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| 262 | Repair(random, child, childTour, ProblemInstance, allowInfeasible);
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| 263 | }
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| 264 |
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| 265 | for (int i = 0; i < p1Clone.Tours.Count; i++) {
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| 266 | Tour childTour = p1Clone.Tours[i].Clone() as Tour;
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| 267 | child.Tours.Add(childTour);
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| 268 | Repair(random, child, childTour, ProblemInstance, allowInfeasible);
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| 269 | }
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| 270 |
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| 271 | //route unrouted customers
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| 272 | child.Unrouted.AddRange(GetUnrouted(child, ProblemInstance.Cities.Value));
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| 273 | bool success = RouteUnrouted(child, allowInfeasible);
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| 274 |
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| 275 | if (success || allowInfeasible)
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| 276 | return child;
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| 277 | else {
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| 278 | if (random.NextDouble() < 0.5)
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| 279 | return parent1.Clone() as PotvinEncoding;
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| 280 | else
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| 281 | return parent2.Clone() as PotvinEncoding;
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| 282 | }
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| 283 | }
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| 284 | }
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| 285 | }
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