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Algorithms 2018,11, 43
Table4.Overallperformancerankings (RPD)ofproposedheuristics inrelation toEMforGroup1and
to thebest foundsolutionforGroup2.
Group1 H6 H5 H2 H1 H4 H3 H9 H8 H10 H7
0.2 0.4 1.1 1.2 3.7 7.0 9.6 16.2 21.1 41.7
Group2 H6 H5 H2 H1 H4 H3 H9 H10 H8 H7
0.2 0.3 0.6 2.4 7.0 11.9 31.4 61.4 68.1 76.6
Theresults fromH6weresimilar to those fromH5whichrankedsecondforoverallperformance
with RPDs of 0.4% inGroup 1 and 0.3% inGroup 2, as shown in Table 4. Both these heuristics
consideredtheEDDruleas the initialorderanditerativelyplacedthefirst tardy jobat theendof the
sequence.However,H6alsoemployedinsertionandpermutationneighborhoodsearches. Therefore,
it canbeseenthat,althoughthis improvementphaseprovidedbetterperformance,H6hadalready
producedverygoodresultsbefore theneighborhoodsearches (explainedbythebehaviorofH5).
Followingtherankings,H2andH1werethirdandfourth, respectively,andbothexhibitedsimilar
behaviorbyconsideringtheEDDruleas the initialorderandthenemployingthe insertionmethod
toconstruct thesequence. Thedifferencebetweenthemis thatH2employsneighborhoodsearches
beforeattemptingto insert thenewjob in thepartial sequence.
Inaddition, itmaybenoted inTable4 that therankings forGroups1and2werealmost thesame,
with thesoleexceptionof the inversionbetweenheuristicsH8andH10 ineighthandninthplaces.
Anotherobservation is that, in thefiveworstmethods, thedeviations inGroup1weremuchlower
thanthose inGroup2which indicatedthat there isagreaterdispersionofsolutionquality formedium
andlarge instances,ascanbeseen inFigure2.
TheworstmethodwasH7which considered theMSTrule as the initial order and iteratively
placed thefirst tardy jobat the endof the sequence. Although it is very similar toH5, as theonly
differencebetweenthemwas in their initialorders (theEDDrulewasused inH5), thediscrepancies in
their resultswerequitesignificant. Thisdemonstratedthat,of the twooptionsusedfor the initial rule,
theEDDwasalwaysmoreadvantageous thantheMST,aswasobvious foreverypairofheuristics
whichwereonlydifferentiatedbytheserules, that is,H1andH3,H2andH4,H5andH7,H6andH8,
andH9andH10.
Tables5–8providedetailedaverageresults for the instancesaccordingto thegroupandsize for
eachheuristic consideringdifferentnumbersof jobsandmachines.
As thenumberof jobsgrows, the fourbestmethods,H6,H5,H2andH1,hadrelativelystable
performances forGroups1 (Table5) andGroup2 (Table6),withvery lowRPDvalues (below1.5).
TheexceptionwasH1forGroup2(Table6),whichhaddecreasingrelativedeviationsrangingfrom
3.9%with15 jobs to0.6%with100. TheotherheuristicshadincreasingRPDvalueswith increasing
numbersof jobs, exceptH7andH8forGroup2whichhaddecreasingvalues for instanceswithupto
100 jobs. Furthermore,H3showedaslightdecrease in instanceswith15 to50 jobs,andanincrease in
thosewith80and100.
Table5.Comparisonofperformances (RPD)ofheuristicsbynumberof jobs forGroup1.
n H1 H2 H3 H4 H5 H6 H7 H8 H9 H10
5 1.0 1.1 5.4 1.8 0.4 0.2 29.1 5.5 5.7 12.7
6 1.2 0.9 7.4 3.4 0.4 0.1 35.8 9.4 7.3 17.7
7 1.2 1.2 6.4 3.4 0.4 0.2 43.9 16.2 8.9 20.0
8 1.5 1.0 7.8 4.8 0.3 0.3 49.3 21.8 11.6 25.3
10 1.2 1.1 8.3 4.9 0.4 0.3 50.6 28.3 14.5 29.8
68
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Buch Algorithms for Scheduling Problems"
Algorithms for Scheduling Problems
- Titel
- Algorithms for Scheduling Problems
- Autoren
- Frank Werner
- Larysa Burtseva
- Yuri Sotskov
- Herausgeber
- MDPI
- Ort
- Basel
- Datum
- 2018
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-03897-120-7
- Abmessungen
- 17.0 x 24.4 cm
- Seiten
- 212
- Schlagwörter
- Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
- Kategorien
- Informatik
- Technik