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Article: Decomposition-based scheduling for makespan minimisation of flexible flow shop with stochastic processing times

TitleDecomposition-based scheduling for makespan minimisation of flexible flow shop with stochastic processing times
Authors
KeywordsBack propagation network
Decomposition
Flexible flow shop
Neighbouring K-means clustering algorithm
Stochastic processing times
Issue Date2010
PublisherInternational Association of Engineers. The Journal's web site is located at http://www.engineeringletters.com/
Citation
Engineering Letters, 2010, v. 18 n. 1, p. 75 How to Cite?
AbstractSince real manufacturing is dynamic and tends to suffer a wide range of uncertainties, research on production scheduling under uncertainty has received much more attention recently. Although various approaches have been developed for scheduling under uncertainty, this problem is still difficult to tackle by any single approach, because of its inherent difficulties. This paper considers makespan minimisation of a flexible flow shop (FFS) scheduling problem with stochastic processing times. It proposes a novel decomposition-based approach (DBA) to decompose an FFS into several machine clusters which can be solved more easily by different approaches. A neighbouring K-means clustering algorithm is developed to firstly group the machines of an FFS into an appropriate number of machine clusters, based on a weighted cluster validity index. A back propagation network (BPN) is then adopted to assign either the shortest processing time (SPT) or the genetic algorithm (GA) to generate a sub-schedule for each machine cluster. If two neighbouring machine clusters are allocated with the same approach, they are subsequently merged. After machine grouping and approach assignment, an overall schedule is generated by integrating the sub-schedules of the clusters. Computation results reveal that the proposed approach is superior to SPT and GA alone for FFS scheduling under stochastic processing times.
Persistent Identifierhttp://hdl.handle.net/10722/124750
ISSN
2015 SCImago Journal Rankings: 0.241
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Ken_HK
dc.contributor.authorChoi, SHen_HK
dc.date.accessioned2010-10-31T10:52:01Z-
dc.date.available2010-10-31T10:52:01Z-
dc.date.issued2010en_HK
dc.identifier.citationEngineering Letters, 2010, v. 18 n. 1, p. 75en_HK
dc.identifier.issn1816-093Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/124750-
dc.description.abstractSince real manufacturing is dynamic and tends to suffer a wide range of uncertainties, research on production scheduling under uncertainty has received much more attention recently. Although various approaches have been developed for scheduling under uncertainty, this problem is still difficult to tackle by any single approach, because of its inherent difficulties. This paper considers makespan minimisation of a flexible flow shop (FFS) scheduling problem with stochastic processing times. It proposes a novel decomposition-based approach (DBA) to decompose an FFS into several machine clusters which can be solved more easily by different approaches. A neighbouring K-means clustering algorithm is developed to firstly group the machines of an FFS into an appropriate number of machine clusters, based on a weighted cluster validity index. A back propagation network (BPN) is then adopted to assign either the shortest processing time (SPT) or the genetic algorithm (GA) to generate a sub-schedule for each machine cluster. If two neighbouring machine clusters are allocated with the same approach, they are subsequently merged. After machine grouping and approach assignment, an overall schedule is generated by integrating the sub-schedules of the clusters. Computation results reveal that the proposed approach is superior to SPT and GA alone for FFS scheduling under stochastic processing times.en_HK
dc.languageengen_HK
dc.publisherInternational Association of Engineers. The Journal's web site is located at http://www.engineeringletters.com/en_HK
dc.relation.ispartofEngineering Lettersen_HK
dc.subjectBack propagation networken_HK
dc.subjectDecompositionen_HK
dc.subjectFlexible flow shopen_HK
dc.subjectNeighbouring K-means clustering algorithmen_HK
dc.subjectStochastic processing timesen_HK
dc.titleDecomposition-based scheduling for makespan minimisation of flexible flow shop with stochastic processing timesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1816-093X&volume=18:1&spage=EL_18_1_09&epage=&date=2010&atitle=Decomposition-Based+Scheduling+for+Makespan+Minimisation+of+Flexible+Flow+Shop+with+Stochastic+Processing+Timesen_HK
dc.identifier.emailChoi, SH:shchoi@hkucc.hku.hken_HK
dc.identifier.authorityChoi, SH=rp00109en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-76549084080en_HK
dc.identifier.hkuros175340en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-76549084080&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume18en_HK
dc.identifier.issue1en_HK
dc.identifier.spageEL_18_1_09en_HK
dc.identifier.spage75-
dc.identifier.epage75-
dc.publisher.placeHong Kongen_HK
dc.identifier.scopusauthoridWang, K=35436577100en_HK
dc.identifier.scopusauthoridChoi, SH=7408119615en_HK

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