1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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 System.Threading;
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26 | using HEAL.Attic;
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27 | using HeuristicLab.Common;
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28 | using HeuristicLab.Core;
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29 | using HeuristicLab.Data;
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30 | using HeuristicLab.Encodings.PermutationEncoding;
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31 | using HeuristicLab.Optimization;
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32 | using HeuristicLab.Parameters;
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33 | using HeuristicLab.Problems.Instances;
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34 | using HeuristicLab.Random;
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35 |
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36 | namespace HeuristicLab.Problems.PTSP {
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37 | [Item("Estimated Probabilistic TSP (pTSP)", "Represents a probabilistic traveling salesman problem where the expected tour length is estimated by averaging over the length of tours on a number of, so called, realizations.")]
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38 | [Creatable(CreatableAttribute.Categories.CombinatorialProblems)]
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39 | [StorableType("d1b4149b-8ab9-4314-8d96-9ea04a4d5b8b")]
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40 | public sealed class EstimatedPTSP : ProbabilisticTSP {
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41 |
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42 | #region Parameter Properties
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43 | [Storable] public IFixedValueParameter<IntValue> RealizationsSeedParameter { get; private set; }
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44 | [Storable] public IFixedValueParameter<IntValue> RealizationsParameter { get; private set; }
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45 | [Storable] private IValueParameter<ReadOnlyItemList<BoolArray>> RealizationDataParameter { get; set; }
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46 | #endregion
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47 |
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48 | #region Properties
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49 |
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50 | public int RealizationsSeed {
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51 | get { return RealizationsSeedParameter.Value.Value; }
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52 | set { RealizationsSeedParameter.Value.Value = value; }
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53 | }
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54 |
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55 | public int Realizations {
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56 | get { return RealizationsParameter.Value.Value; }
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57 | set { RealizationsParameter.Value.Value = value; }
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58 | }
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59 |
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60 | private ReadOnlyItemList<BoolArray> RealizationData {
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61 | get { return RealizationDataParameter.Value; }
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62 | set { RealizationDataParameter.Value = value; }
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63 | }
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64 | #endregion
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65 |
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66 | [StorableConstructor]
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67 | private EstimatedPTSP(StorableConstructorFlag _) : base(_) { }
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68 | private EstimatedPTSP(EstimatedPTSP original, Cloner cloner)
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69 | : base(original, cloner) {
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70 | RealizationsSeedParameter = cloner.Clone(original.RealizationsSeedParameter);
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71 | RealizationsParameter = cloner.Clone(original.RealizationsParameter);
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72 | RealizationDataParameter = cloner.Clone(original.RealizationDataParameter);
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73 | RegisterEventHandlers();
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74 | }
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75 | public EstimatedPTSP() {
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76 | Parameters.Add(RealizationsSeedParameter = new FixedValueParameter<IntValue>("RealizationsSeed", "The starting seed of the RNG from which realizations should be drawn.", new IntValue(1)));
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77 | Parameters.Add(RealizationsParameter = new FixedValueParameter<IntValue>("Realizations", "The number of realizations that should be made.", new IntValue(100)));
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78 | Parameters.Add(RealizationDataParameter = new ValueParameter<ReadOnlyItemList<BoolArray>>("RealizationData", "The actual realizations.") { Hidden = true, GetsCollected = false });
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79 |
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80 | Operators.Add(new PTSPEstimatedInversionMoveEvaluator());
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81 | Operators.Add(new PTSPEstimatedInsertionMoveEvaluator());
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82 | Operators.Add(new PTSPEstimatedInversionLocalImprovement());
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83 | Operators.Add(new PTSPEstimatedInsertionLocalImprovement());
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84 | Operators.Add(new PTSPEstimatedTwoPointFiveLocalImprovement());
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85 |
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86 | Operators.Add(new ExhaustiveTwoPointFiveMoveGenerator());
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87 | Operators.Add(new StochasticTwoPointFiveMultiMoveGenerator());
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88 | Operators.Add(new StochasticTwoPointFiveSingleMoveGenerator());
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89 | Operators.Add(new TwoPointFiveMoveMaker());
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90 | Operators.Add(new PTSPEstimatedTwoPointFiveMoveEvaluator());
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91 |
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92 | Encoding.ConfigureOperators(Operators.OfType<IOperator>());
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93 | foreach (var twopointfiveMoveOperator in Operators.OfType<ITwoPointFiveMoveOperator>()) {
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94 | twopointfiveMoveOperator.TwoPointFiveMoveParameter.ActualName = "Permutation.TwoPointFiveMove";
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95 | }
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96 |
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97 | UpdateRealizations();
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98 | RegisterEventHandlers();
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99 | }
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100 |
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101 | public override IDeepCloneable Clone(Cloner cloner) {
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102 | return new EstimatedPTSP(this, cloner);
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103 | }
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104 |
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105 | public override ISingleObjectiveEvaluationResult Evaluate(Permutation tour, IRandom random, CancellationToken cancellationToken) {
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106 | var quality = Evaluate(tour, ProbabilisticTSPData, RealizationData, cancellationToken);
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107 | return new SingleObjectiveEvaluationResult(quality);
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108 | }
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109 |
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110 | [StorableHook(HookType.AfterDeserialization)]
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111 | private void AfterDeserialization() {
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112 | RegisterEventHandlers();
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113 | }
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114 |
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115 | public static double Evaluate(Permutation tour, IProbabilisticTSPData data, IEnumerable<BoolArray> realizations, CancellationToken cancellationToken) {
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116 | // Estimation-based evaluation, here without calculating variance for faster evaluation
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117 | var estimatedSum = 0.0;
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118 | var count = 0;
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119 | foreach (var r in realizations) {
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120 | int singleRealization = -1, firstNode = -1;
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121 | for (var j = 0; j < data.Cities; j++) {
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122 | if (r[tour[j]]) {
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123 | if (singleRealization != -1) {
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124 | estimatedSum += data.GetDistance(singleRealization, tour[j]);
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125 | } else {
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126 | firstNode = tour[j];
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127 | }
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128 | singleRealization = tour[j];
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129 | }
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130 | }
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131 | if (singleRealization != -1)
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132 | estimatedSum += data.GetDistance(singleRealization, firstNode);
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133 | count++;
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134 | }
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135 | return estimatedSum / count;
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136 | }
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137 |
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138 | /// <summary>
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139 | /// An evaluate method that can be used if mean as well as variance should be calculated
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140 | /// </summary>
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141 | /// <param name="tour">The tour between all cities.</param>
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142 | /// <param name="data">The main parameters of the pTSP.</param>
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143 | /// <param name="realizations">How many realizations to achieve.</param>
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144 | /// <param name="seed">The starting seed of generating the realizations.</param>
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145 | /// <param name="variance">The estimated variance will be returned in addition to the mean.</param>
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146 | /// <returns>A vector with length two containing mean and variance.</returns>
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147 | public static double Evaluate(Permutation tour, IProbabilisticTSPData data, IEnumerable<BoolArray> realizations, out double variance) {
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148 | // Estimation-based evaluation
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149 | var estimatedSum = 0.0;
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150 | var partialSums = new List<double>();
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151 | var count = 0;
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152 | foreach (var r in realizations) {
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153 | var pSum = 0.0;
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154 | int singleRealization = -1, firstNode = -1;
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155 | for (var j = 0; j < data.Cities; j++) {
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156 | if (r[tour[j]]) {
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157 | if (singleRealization != -1) {
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158 | pSum += data.GetDistance(singleRealization, tour[j]);
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159 | } else {
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160 | firstNode = tour[j];
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161 | }
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162 | singleRealization = tour[j];
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163 | }
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164 | }
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165 | if (singleRealization != -1) {
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166 | pSum += data.GetDistance(singleRealization, firstNode);
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167 | }
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168 | estimatedSum += pSum;
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169 | partialSums.Add(pSum);
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170 | count++;
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171 | }
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172 | var mean = estimatedSum / count;
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173 | variance = 0.0;
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174 | for (var i = 0; i < count; i++) {
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175 | variance += Math.Pow((partialSums[i] - mean), 2);
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176 | }
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177 | variance = variance / count;
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178 | return mean;
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179 | }
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180 |
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181 | private void RegisterEventHandlers() {
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182 | RealizationsParameter.Value.ValueChanged += RealizationsOnChanged;
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183 | RealizationsSeedParameter.Value.ValueChanged += RealizationsSeedOnChanged;
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184 | }
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185 |
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186 | private void RealizationsSeedOnChanged(object sender, EventArgs e) {
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187 | UpdateRealizations();
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188 | }
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189 |
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190 | private void RealizationsOnChanged(object sender, EventArgs e) {
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191 | if (Realizations <= 0) Realizations = 1;
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192 | else UpdateRealizations();
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193 | }
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194 |
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195 | public override void Load(PTSPData data) {
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196 | base.Load(data);
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197 | UpdateRealizations();
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198 | }
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199 |
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200 | private void UpdateRealizations() {
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201 | var data = new List<BoolArray>(Realizations);
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202 | var rng = new MersenneTwister((uint)RealizationsSeed);
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203 | if (Enumerable.Range(0, ProbabilisticTSPData.Cities).All(c => ProbabilisticTSPData.GetProbability(c) <= 0))
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204 | throw new InvalidOperationException("All probabilities are zero.");
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205 | while (data.Count < Realizations) {
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206 | var cities = 0;
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207 | var r = new bool[ProbabilisticTSPData.Cities];
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208 | for (var j = 0; j < ProbabilisticTSPData.Cities; j++) {
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209 | if (rng.NextDouble() < ProbabilisticTSPData.GetProbability(j)) {
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210 | r[j] = true;
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211 | cities++;
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212 | }
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213 | }
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214 | if (cities > 0) {
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215 | data.Add(new BoolArray(r, @readonly: true));
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216 | }
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217 | }
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218 | RealizationData = (new ItemList<BoolArray>(data)).AsReadOnly();
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219 | }
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220 | }
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221 | } |
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