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 HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Encodings.ScheduleEncoding;
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26 | using HeuristicLab.Encodings.ScheduleEncoding.PriorityRulesVector;
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27 | using HeuristicLab.Optimization;
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28 | using HeuristicLab.Parameters;
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29 | using HEAL.Attic;
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30 |
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31 | namespace HeuristicLab.Problems.Scheduling {
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32 | [Item("JobSequencingMatrixDecoder", "Applies the GifflerThompson algorithm to create an active schedule from a JobSequencing Matrix.")]
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33 | [StorableType("4BECE53D-C72B-4F96-AE96-EA01E7DE4B92")]
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34 | public class PRVDecoder : ScheduleDecoder, IStochasticOperator, IJSSPOperator {
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35 |
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36 | public ILookupParameter<IRandom> RandomParameter {
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37 | get { return (LookupParameter<IRandom>)Parameters["Random"]; }
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38 | }
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39 | public ILookupParameter<ItemList<Job>> JobDataParameter {
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40 | get { return (LookupParameter<ItemList<Job>>)Parameters["JobData"]; }
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41 | }
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42 |
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43 | #region Priority Rules
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44 | //smallest number of remaining tasks
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45 | private Task FILORule(ItemList<Task> tasks) {
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46 | Task currentResult = tasks[tasks.Count - 1];
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47 | return currentResult;
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48 | }
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49 |
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50 | //earliest start time
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51 | private Task ESTRule(ItemList<Task> tasks, Schedule schedule) {
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52 | Task currentResult = RandomRule(tasks);
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53 | double currentEST = double.MaxValue;
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54 | foreach (Task t in tasks) {
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55 | double est = GTAlgorithmUtils.ComputeEarliestStartTime(t, schedule);
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56 | if (est < currentEST) {
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57 | currentEST = est;
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58 | currentResult = t;
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59 | }
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60 | }
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61 | return currentResult;
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62 | }
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63 |
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64 | //shortest processingtime
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65 | private Task SPTRule(ItemList<Task> tasks) {
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66 | Task currentResult = RandomRule(tasks);
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67 | foreach (Task t in tasks) {
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68 | if (t.Duration < currentResult.Duration)
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69 | currentResult = t;
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70 | }
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71 | return currentResult;
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72 | }
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73 |
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74 | //longest processing time
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75 | private Task LPTRule(ItemList<Task> tasks) {
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76 | Task currentResult = RandomRule(tasks);
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77 | foreach (Task t in tasks) {
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78 | if (t.Duration > currentResult.Duration)
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79 | currentResult = t;
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80 | }
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81 | return currentResult;
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82 | }
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83 |
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84 | //most work remaining
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85 | private Task MWRRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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86 | Task currentResult = RandomRule(tasks);
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87 | double currentLargestRemainingProcessingTime = 0;
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88 | foreach (Task t in tasks) {
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89 | double remainingProcessingTime = 0;
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90 | foreach (Task jt in jobs[t.JobNr].Tasks) {
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91 | if (!jt.IsScheduled)
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92 | remainingProcessingTime += jt.Duration;
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93 | }
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94 | if (remainingProcessingTime > currentLargestRemainingProcessingTime) {
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95 | currentLargestRemainingProcessingTime = remainingProcessingTime;
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96 | currentResult = t;
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97 | }
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98 | }
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99 | return currentResult;
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100 | }
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101 |
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102 | //least work remaining
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103 | private Task LWRRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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104 | Task currentResult = RandomRule(tasks);
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105 | double currentSmallestRemainingProcessingTime = double.MaxValue;
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106 | foreach (Task t in tasks) {
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107 | double remainingProcessingTime = 0;
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108 | foreach (Task jt in jobs[t.JobNr].Tasks) {
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109 | if (!jt.IsScheduled)
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110 | remainingProcessingTime += jt.Duration;
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111 | }
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112 | if (remainingProcessingTime < currentSmallestRemainingProcessingTime) {
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113 | currentSmallestRemainingProcessingTime = remainingProcessingTime;
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114 | currentResult = t;
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115 | }
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116 | }
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117 | return currentResult;
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118 | }
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119 |
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120 | //most operations remaining
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121 | private Task MORRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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122 | Task currentResult = RandomRule(tasks);
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123 | int currentLargestNrOfRemainingTasks = 0;
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124 | foreach (Task t in tasks) {
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125 | int nrOfRemainingTasks = 0;
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126 | foreach (Task jt in jobs[t.JobNr].Tasks) {
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127 | if (!jt.IsScheduled)
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128 | nrOfRemainingTasks++;
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129 | }
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130 | if (currentLargestNrOfRemainingTasks < nrOfRemainingTasks) {
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131 | currentLargestNrOfRemainingTasks = nrOfRemainingTasks;
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132 | currentResult = t;
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133 | }
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134 | }
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135 | return currentResult;
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136 | }
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137 |
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138 | //least operationsremaining
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139 | private Task LORRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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140 | Task currentResult = RandomRule(tasks);
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141 | int currentSmallestNrOfRemainingTasks = int.MaxValue;
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142 | foreach (Task t in tasks) {
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143 | int nrOfRemainingTasks = 0;
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144 | foreach (Task jt in jobs[t.JobNr].Tasks) {
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145 | if (!jt.IsScheduled)
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146 | nrOfRemainingTasks++;
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147 | }
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148 | if (currentSmallestNrOfRemainingTasks > nrOfRemainingTasks) {
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149 | currentSmallestNrOfRemainingTasks = nrOfRemainingTasks;
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150 | currentResult = t;
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151 | }
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152 | }
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153 | return currentResult;
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154 | }
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155 |
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156 | //first operation in Queue
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157 | private Task FIFORule(ItemList<Task> tasks) {
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158 | Task currentResult = tasks[0];
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159 | return currentResult;
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160 | }
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161 |
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162 | //random
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163 | private Task RandomRule(ItemList<Task> tasks) {
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164 | Task currentResult = tasks[RandomParameter.ActualValue.Next(tasks.Count)];
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165 | return currentResult;
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166 | }
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167 |
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168 | #endregion
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169 |
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170 | [StorableConstructor]
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171 | protected PRVDecoder(StorableConstructorFlag _) : base(_) { }
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172 | protected PRVDecoder(PRVDecoder original, Cloner cloner) : base(original, cloner) { }
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173 | public PRVDecoder()
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174 | : base() {
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175 | Parameters.Add(new LookupParameter<IRandom>("Random", "The pseudo random number generator which should be used for stochastic manipulation operators."));
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176 | Parameters.Add(new LookupParameter<ItemList<Job>>("JobData", "Job data taken from the SchedulingProblem - Instance."));
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177 | ScheduleEncodingParameter.ActualName = "PriorityRulesVector";
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178 | }
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179 |
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180 | public override IDeepCloneable Clone(Cloner cloner) {
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181 | return new PRVDecoder(this, cloner);
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182 | }
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183 |
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184 | private Task SelectTaskFromConflictSet(ItemList<Task> conflictSet, int ruleIndex, int nrOfRules, Schedule schedule, ItemList<Job> jobs) {
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185 | if (conflictSet.Count == 1)
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186 | return conflictSet[0];
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187 |
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188 | ruleIndex = ruleIndex % nrOfRules;
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189 | switch (ruleIndex) {
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190 | case 0: return FILORule(conflictSet);
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191 | case 1: return ESTRule(conflictSet, schedule);
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192 | case 2: return SPTRule(conflictSet);
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193 | case 3: return LPTRule(conflictSet);
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194 | case 4: return MWRRule(conflictSet, jobs);
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195 | case 5: return LWRRule(conflictSet, jobs);
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196 | case 6: return MORRule(conflictSet, jobs);
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197 | case 7: return LORRule(conflictSet, jobs);
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198 | case 8: return FIFORule(conflictSet);
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199 | case 9: return RandomRule(conflictSet);
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200 | default: return RandomRule(conflictSet);
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201 | }
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202 | }
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203 |
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204 | public override Schedule CreateScheduleFromEncoding(IScheduleEncoding encoding) {
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205 | var solution = encoding as PRVEncoding;
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206 | if (solution == null) throw new InvalidOperationException("Encoding is not of type PWREncoding");
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207 |
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208 | var jobs = (ItemList<Job>)JobDataParameter.ActualValue.Clone();
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209 | var resultingSchedule = new Schedule(jobs[0].Tasks.Count);
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210 |
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211 | //Reset scheduled tasks in result
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212 | foreach (Job j in jobs) {
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213 | foreach (Task t in j.Tasks) {
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214 | t.IsScheduled = false;
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215 | }
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216 | }
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217 |
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218 | //GT-Algorithm
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219 | //STEP 0 - Compute a list of "earliest operations"
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220 | ItemList<Task> earliestTasksList = GTAlgorithmUtils.GetEarliestNotScheduledTasks(jobs);
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221 | //int currentDecisionIndex = 0;
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222 | while (earliestTasksList.Count > 0) {
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223 | //STEP 1 - Get earliest not scheduled operation with minimal earliest completing time
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224 | Task minimal = GTAlgorithmUtils.GetTaskWithMinimalEC(earliestTasksList, resultingSchedule);
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225 |
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226 | //STEP 2 - Compute a conflict set of all operations that can be scheduled on the machine the previously selected operation runs on
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227 | ItemList<Task> conflictSet = GTAlgorithmUtils.GetConflictSetForTask(minimal, earliestTasksList, jobs, resultingSchedule);
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228 |
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229 | //STEP 3 - Select an operation from the conflict set (various methods depending on how the algorithm should work..)
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230 | //Task selectedTask = SelectTaskFromConflictSet(conflictSet, solution.PriorityRulesVector [currentDecisionIndex++], solution.NrOfRules.Value);
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231 | Task selectedTask = SelectTaskFromConflictSet(conflictSet, solution.PriorityRulesVector[minimal.JobNr], solution.NrOfRules.Value, resultingSchedule, jobs);
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232 |
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233 | //STEP 4 - Adding the selected operation to the current schedule
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234 | selectedTask.IsScheduled = true;
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235 | double startTime = GTAlgorithmUtils.ComputeEarliestStartTime(selectedTask, resultingSchedule);
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236 | resultingSchedule.ScheduleTask(selectedTask.ResourceNr, startTime, selectedTask.Duration, selectedTask.JobNr);
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237 |
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238 | //STEP 5 - Back to STEP 1
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239 | earliestTasksList = GTAlgorithmUtils.GetEarliestNotScheduledTasks(jobs);
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240 | }
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241 |
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242 | return resultingSchedule;
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243 | }
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244 | }
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245 | }
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