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Algorithms 2018,11, 43 Figure1. Exampleofdifferent scheduleswith the samesequenceof jobs: (a) only J3 is just-in-time; (b) J2 and J1 are just-in-time;and(c) J2 and J3 are just-in-time. Therefore, theEMenumeratesallpossiblesequences,but it is impractical toprobeallpossible schedules,especially formediumandlargescale instances.Giventhat, theEMwasnotappliedfor Group2’s instances,andthebest solutionfoundbytheheuristicsH1–H10wasconsideredasreference for the instances in thisgroup. EnumerationMethod Step1.Enumerate then! possiblesequencesandconsider theonewith thebestnJIT. Step2.Apply the timingadjustmentprocedure. Algorithm12.Pseudo-codeof theenumerationmethod. Figure 2 graphically presents the results, with 95% confidence intervals of the averageRPD obtainedbyeachheuristicmethodforbothGroups1and2. The95%confidence intervalmeans that theresults (RPD)of95casesamong100arewithin thedisplayedrange. Theglobalanalysisof results revealedthatH6clearlyoutperformedtheotherheuristics,witha RPDof0.2%forbothGroups1and2(ascanbeseen inTable4)which indicates that itprovidedthe bestorveryclose to thebest solutions formanycases. Figure2.Comparisonofperformancesofheuristicsbygroupwith95%confidence intervalofaverage RPD: (a) relatedtoEMforGroup1;and(b) relatedto thebestH1–H10solutionforGroup2. 67
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Algorithms for Scheduling Problems
Title
Algorithms for Scheduling Problems
Authors
Frank Werner
Larysa Burtseva
Yuri Sotskov
Editor
MDPI
Location
Basel
Date
2018
Language
English
License
CC BY 4.0
ISBN
978-3-03897-120-7
Size
17.0 x 24.4 cm
Pages
212
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Categories
Informatik
Technik
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Algorithms for Scheduling Problems