[15661] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2018 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.Linq;
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Encodings.PermutationEncoding;
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[16011] | 28 | using HeuristicLab.Optimization;
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[15661] | 29 | using HeuristicLab.Parameters;
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| 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 31 | using HeuristicLab.Problems.Instances;
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| 32 |
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| 33 |
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| 34 | namespace HeuristicLab.Problems.PermutationProblems {
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| 35 | [Item("Permutation Flowshop Scheduling Problem (PFSP)", "Represents a Permutation Flowshop Scheduling Problem")]
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| 36 | [Creatable(CreatableAttribute.Categories.CombinatorialProblems)]
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| 37 | [StorableClass]
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| 38 | public sealed class PermutationFlowshopSchedulingProblem : SingleObjectiveBasicProblem<PermutationEncoding>, IProblemInstanceConsumer<FSSPData>, IProblemInstanceExporter<FSSPData> {
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| 39 | #region Fields
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| 40 | private static readonly FSSPData DefaultInstance = new FSSPData() {
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| 41 | Name = "Permutation Flowshop Scheduling Problem (PFSP)",
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| 42 | Description = "The default instance of the PFSP problem in HeuristicLab",
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| 43 | Jobs = 4,
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| 44 | Machines = 4,
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| 45 | //BestKnownQuality = 328,
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| 46 | ProcessingTimes = new double[,] {
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| 47 | {5 ,3, 6 ,6 },
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| 48 | {2 ,4, 8 ,4},
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| 49 | {4 ,2, 7 ,4},
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| 50 | {5 ,3, 8 ,6}
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| 51 | }
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| 52 | };
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| 53 | public event EventHandler BestKnownSolutionChanged;
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| 54 | #endregion
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| 55 |
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| 56 | #region Getter/Setter
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| 57 | public OptionalValueParameter<Permutation> BestKnownSolutionParameter
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| 58 | {
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| 59 | get { return (OptionalValueParameter<Permutation>)Parameters["BestKnownSolution"]; }
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| 60 | }
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| 61 | public OptionalValueParameter<DoubleMatrix> JobMatrixParameter
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| 62 | {
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| 63 | get { return (OptionalValueParameter<DoubleMatrix>)Parameters["JobMatrix"]; }
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| 64 | }
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| 65 | public Permutation BestKnownSolution
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| 66 | {
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| 67 | get { return BestKnownSolutionParameter.Value; }
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| 68 | set
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| 69 | {
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| 70 | BestKnownSolutionParameter.Value = value;
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| 71 | if (BestKnownSolutionChanged != null) { OnBestKnownSolutionChanged(); }
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| 72 | }
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| 73 | }
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| 74 | public DoubleMatrix JobMatrix
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| 75 | {
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| 76 | get { return JobMatrixParameter.Value; }
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| 77 | set { JobMatrixParameter.Value = value; }
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| 78 | }
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| 79 |
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| 80 | public override bool Maximization { get { return false; } }
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| 81 | #endregion
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| 82 |
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| 83 | #region Ctor
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| 84 | [StorableConstructor]
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| 85 | private PermutationFlowshopSchedulingProblem(bool deserializing) : base(deserializing) { }
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| 86 | private PermutationFlowshopSchedulingProblem(PermutationFlowshopSchedulingProblem original, Cloner cloner) : base(original, cloner) { }
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| 87 | public PermutationFlowshopSchedulingProblem() {
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| 88 | Parameters.Add(new OptionalValueParameter<Permutation>("BestKnownSolution", "The best known solution of this FSSP instance."));
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| 89 | Parameters.Add(new OptionalValueParameter<DoubleMatrix>("JobMatrix", "The matrix which contains the jobs,machines and duration."));
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| 90 |
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| 91 | Load(DefaultInstance);
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| 92 | EvaluatorParameter.GetsCollected = false;
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| 93 | EvaluatorParameter.Hidden = true;
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| 94 |
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| 95 | Evaluator.QualityParameter.ActualName = "Makespan";
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| 96 | }
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| 97 | #endregion
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| 98 |
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| 99 | #region Methods
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| 100 | public override IDeepCloneable Clone(Cloner cloner) {
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| 101 | return new PermutationFlowshopSchedulingProblem(this, cloner);
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| 102 | }
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| 103 |
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| 104 | public void Load(FSSPData data) {
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| 105 | if (data.BestKnownQuality.HasValue) {
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| 106 | BestKnownQuality = data.BestKnownQuality.Value;
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| 107 | }
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| 108 | Name = data.Name;
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| 109 | Description = data.Description;
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| 110 | JobMatrix = new DoubleMatrix(data.ProcessingTimes);
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| 111 | Encoding.Length = JobMatrix.Columns;
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| 112 |
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| 113 | if (data.BestKnownSchedule != null) {
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| 114 | int[] permut = data.BestKnownSchedule;
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| 115 | //Clean up if the first index = 1
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| 116 | if (!permut.Contains(0)) { permut = permut.Select(v => v - 1).ToArray(); }
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| 117 |
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| 118 | BestKnownSolution = new Permutation(PermutationTypes.Absolute, data.BestKnownSchedule);
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| 119 | BestKnownQuality = Evaluate(permut, JobMatrix);
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| 120 | }
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| 121 | }
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| 122 | public FSSPData Export() {
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| 123 | var result = new FSSPData {
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| 124 | Name = Name,
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| 125 | Description = Description,
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| 126 | ProcessingTimes = new double[JobMatrix.Rows, JobMatrix.Columns]
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| 127 | };
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| 128 |
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| 129 | result.BestKnownQuality = BestKnownQuality;
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| 130 |
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| 131 | if (JobMatrix != null) {
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| 132 | result.Jobs = JobMatrix.Rows;
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| 133 | result.Machines = JobMatrix.Columns;
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| 134 | }
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| 135 |
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| 136 | for (int i = 0; i < JobMatrix.Rows; i++) {
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| 137 | for (int j = 0; j < JobMatrix.Columns; j++) {
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| 138 | result.ProcessingTimes[i, j] = JobMatrix[i, j];
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| 139 | }
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| 140 | }
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| 141 |
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| 142 | result.BestKnownSchedule = BestKnownSolution != null ? (BestKnownSolution as IntArray).ToArray() : null;
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| 143 |
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| 144 | return result;
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| 145 | }
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| 146 |
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| 147 | public override double Evaluate(Individual individual, IRandom random) {
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| 148 | return Evaluate(individual.Permutation().ToArray(), JobMatrix);
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| 149 | }
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| 150 | #endregion
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| 151 |
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| 152 | #region Helper Methods
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| 153 | private void OnBestKnownSolutionChanged() {
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| 154 | BestKnownSolutionChanged?.Invoke(this, EventArgs.Empty);
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| 155 | }
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| 156 |
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| 157 | /// <summary>
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| 158 | /// Calculates the makespan (cMax), meaning the total time from start till the last job on the last machine is done
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| 159 | /// </summary>
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| 160 | /// <param name="permutation"></param>
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| 161 | /// <param name="matrix"></param>
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| 162 | /// <returns></returns>
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| 163 | private double Evaluate(int[] permutation, DoubleMatrix matrix) {
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| 164 | DoubleMatrix calculatedTime = new DoubleMatrix(matrix.Rows, matrix.Columns);
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| 165 | double runtimePrev;
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| 166 |
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| 167 | double runtimePrevMachine;
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| 168 | double runtimePrevJobOnThisMachine;
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| 169 |
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| 170 | for (var machineIdx = 0; machineIdx < matrix.Rows; machineIdx++) {
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| 171 | for (var jobIdx = 0; jobIdx < matrix.Columns; jobIdx++) {
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| 172 | runtimePrev = 0;
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| 173 |
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| 174 | if (jobIdx == 0 && machineIdx == 0) { //Nothing to calculate
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| 175 | } else if (machineIdx == 0) {
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| 176 | runtimePrev = calculatedTime[machineIdx, jobIdx - 1];
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| 177 | } else if (jobIdx == 0) {
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| 178 | runtimePrev = calculatedTime[machineIdx - 1, jobIdx];
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| 179 | } else {
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| 180 | runtimePrevMachine = calculatedTime[machineIdx - 1, jobIdx];
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| 181 | runtimePrevJobOnThisMachine = calculatedTime[machineIdx, jobIdx - 1];
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| 182 | runtimePrev = runtimePrevMachine > runtimePrevJobOnThisMachine ? runtimePrevMachine : runtimePrevJobOnThisMachine;
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| 183 | }
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| 184 | calculatedTime[machineIdx, jobIdx] = matrix[machineIdx, permutation[jobIdx]] + runtimePrev;
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| 185 | }
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| 186 | }
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| 187 | return calculatedTime[calculatedTime.Rows - 1, calculatedTime.Columns - 1];
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| 188 | }
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| 189 | #endregion
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| 190 | }
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| 191 | }
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