[6293] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[14186] | 3 | * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[6293] | 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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[8887] | 22 | using System;
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[6406] | 23 | using HeuristicLab.Common;
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[6293] | 24 | using HeuristicLab.Core;
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[6406] | 25 | using HeuristicLab.Encodings.ScheduleEncoding;
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| 26 | using HeuristicLab.Encodings.ScheduleEncoding.PriorityRulesVector;
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[6293] | 27 | using HeuristicLab.Optimization;
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| 28 | using HeuristicLab.Parameters;
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[6406] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[6293] | 30 |
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[6406] | 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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[6293] | 33 | [StorableClass]
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[8887] | 34 | public class PRVDecoder : ScheduleDecoder, IStochasticOperator, IJSSPOperator {
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| 35 |
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[6293] | 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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[6406] | 46 | Task currentResult = tasks[tasks.Count - 1];
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[6293] | 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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[8887] | 51 | private Task ESTRule(ItemList<Task> tasks, Schedule schedule) {
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[6293] | 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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[8887] | 55 | double est = GTAlgorithmUtils.ComputeEarliestStartTime(t, schedule);
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[6293] | 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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[6406] | 63 |
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[6293] | 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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[6412] | 68 | if (t.Duration < currentResult.Duration)
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[6293] | 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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[6412] | 78 | if (t.Duration > currentResult.Duration)
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[6293] | 79 | currentResult = t;
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| 80 | }
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| 81 | return currentResult;
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[6406] | 82 | }
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[6293] | 83 |
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| 84 | //most work remaining
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[8887] | 85 | private Task MWRRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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[6293] | 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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[6412] | 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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[6293] | 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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[6406] | 101 |
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[6293] | 102 | //least work remaining
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[8887] | 103 | private Task LWRRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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[6293] | 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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[6412] | 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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[6293] | 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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[8887] | 121 | private Task MORRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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[6293] | 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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[6412] | 126 | foreach (Task jt in jobs[t.JobNr].Tasks) {
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| 127 | if (!jt.IsScheduled)
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[6293] | 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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[6406] | 137 |
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[6293] | 138 | //least operationsremaining
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[8887] | 139 | private Task LORRule(ItemList<Task> tasks, ItemList<Job> jobs) {
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[6293] | 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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[6412] | 144 | foreach (Task jt in jobs[t.JobNr].Tasks) {
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| 145 | if (!jt.IsScheduled)
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[6293] | 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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[6406] | 155 |
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[6293] | 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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[6406] | 161 |
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[6293] | 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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[6406] | 170 | [StorableConstructor]
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| 171 | protected PRVDecoder(bool deserializing) : base(deserializing) { }
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[8887] | 172 | protected PRVDecoder(PRVDecoder original, Cloner cloner) : base(original, cloner) { }
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[6293] | 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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[6406] | 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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[6293] | 178 | }
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| 179 |
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[8887] | 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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[6293] | 185 | if (conflictSet.Count == 1)
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| 186 | return conflictSet[0];
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[6364] | 187 |
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[6293] | 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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[8887] | 191 | case 1: return ESTRule(conflictSet, schedule);
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[6293] | 192 | case 2: return SPTRule(conflictSet);
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| 193 | case 3: return LPTRule(conflictSet);
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[8887] | 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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[6293] | 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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[6364] | 201 | }
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[6293] | 202 | }
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| 203 |
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[8887] | 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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[6293] | 207 |
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[8887] | 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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[6293] | 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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[6412] | 214 | t.IsScheduled = false;
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[6293] | 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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[6364] | 220 | ItemList<Task> earliestTasksList = GTAlgorithmUtils.GetEarliestNotScheduledTasks(jobs);
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| 221 | //int currentDecisionIndex = 0;
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[6293] | 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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[6364] | 224 | Task minimal = GTAlgorithmUtils.GetTaskWithMinimalEC(earliestTasksList, resultingSchedule);
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[6293] | 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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[6364] | 227 | ItemList<Task> conflictSet = GTAlgorithmUtils.GetConflictSetForTask(minimal, earliestTasksList, jobs, resultingSchedule);
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[6293] | 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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[6364] | 230 | //Task selectedTask = SelectTaskFromConflictSet(conflictSet, solution.PriorityRulesVector [currentDecisionIndex++], solution.NrOfRules.Value);
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[8887] | 231 | Task selectedTask = SelectTaskFromConflictSet(conflictSet, solution.PriorityRulesVector[minimal.JobNr], solution.NrOfRules.Value, resultingSchedule, jobs);
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[6293] | 232 |
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| 233 | //STEP 4 - Adding the selected operation to the current schedule
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[6412] | 234 | selectedTask.IsScheduled = true;
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[6406] | 235 | double startTime = GTAlgorithmUtils.ComputeEarliestStartTime(selectedTask, resultingSchedule);
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[6412] | 236 | resultingSchedule.ScheduleTask(selectedTask.ResourceNr, startTime, selectedTask.Duration, selectedTask.JobNr);
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[6293] | 237 |
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| 238 | //STEP 5 - Back to STEP 1
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[6364] | 239 | earliestTasksList = GTAlgorithmUtils.GetEarliestNotScheduledTasks(jobs);
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[6293] | 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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