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Article: Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach

TitleSolving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach
Authors
KeywordsDistributed scheduling
Flexible manufacturing systems
Genetic algorithms
Maintenance
Issue Date2006
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/rcim
Citation
Robotics And Computer-Integrated Manufacturing, 2006, v. 22 n. 5-6, p. 493-504 How to Cite?
AbstractIn general, distributed scheduling problem focuses on simultaneously solving two issues: (i) allocation of jobs to suitable factories and (ii) determination of the corresponding production scheduling in each factory. The objective of this approach is to maximize the system efficiency by finding an optimal planning for a better collaboration among various processes. This makes distributed scheduling problems more complicated than classical production scheduling ones. With the addition of alternative production routing, the problems are even more complicated. Conventionally, machines are usually assumed to be available without interruption during the production scheduling. Maintenance is not considered. However, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it influences the production scheduling. In this connection, maintenance should be considered in distributed scheduling. The objective of this paper is to propose a genetic algorithm with dominant genes (GADG) approach to deal with distributed flexible manufacturing system (FMS) scheduling problems subject to machine maintenance constraint. The optimization performance of the proposed GADG will be compared with other existing approaches, such as simple genetic algorithms to demonstrate its reliability. The significance and benefits of considering maintenance in distributed scheduling will also be demonstrated by simulation runs on a sample problem. © 2006 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74593
ISSN
2015 Impact Factor: 2.077
2015 SCImago Journal Rankings: 1.621
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorChung, SHen_HK
dc.contributor.authorChan, LYen_HK
dc.contributor.authorFinke, Gen_HK
dc.contributor.authorTiwari, MKen_HK
dc.date.accessioned2010-09-06T07:02:52Z-
dc.date.available2010-09-06T07:02:52Z-
dc.date.issued2006en_HK
dc.identifier.citationRobotics And Computer-Integrated Manufacturing, 2006, v. 22 n. 5-6, p. 493-504en_HK
dc.identifier.issn0736-5845en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74593-
dc.description.abstractIn general, distributed scheduling problem focuses on simultaneously solving two issues: (i) allocation of jobs to suitable factories and (ii) determination of the corresponding production scheduling in each factory. The objective of this approach is to maximize the system efficiency by finding an optimal planning for a better collaboration among various processes. This makes distributed scheduling problems more complicated than classical production scheduling ones. With the addition of alternative production routing, the problems are even more complicated. Conventionally, machines are usually assumed to be available without interruption during the production scheduling. Maintenance is not considered. However, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it influences the production scheduling. In this connection, maintenance should be considered in distributed scheduling. The objective of this paper is to propose a genetic algorithm with dominant genes (GADG) approach to deal with distributed flexible manufacturing system (FMS) scheduling problems subject to machine maintenance constraint. The optimization performance of the proposed GADG will be compared with other existing approaches, such as simple genetic algorithms to demonstrate its reliability. The significance and benefits of considering maintenance in distributed scheduling will also be demonstrated by simulation runs on a sample problem. © 2006 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/rcimen_HK
dc.relation.ispartofRobotics and Computer-Integrated Manufacturingen_HK
dc.subjectDistributed schedulingen_HK
dc.subjectFlexible manufacturing systemsen_HK
dc.subjectGenetic algorithmsen_HK
dc.subjectMaintenanceen_HK
dc.titleSolving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approachen_HK
dc.typeArticleen_HK
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hken_HK
dc.identifier.emailChan, LY: plychan@hku.hken_HK
dc.identifier.authorityChan, FTS=rp00090en_HK
dc.identifier.authorityChan, LY=rp00093en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.rcim.2005.11.005en_HK
dc.identifier.scopuseid_2-s2.0-33746855485en_HK
dc.identifier.hkuros136076en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33746855485&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume22en_HK
dc.identifier.issue5-6en_HK
dc.identifier.spage493en_HK
dc.identifier.epage504en_HK
dc.identifier.isiWOS:000240228600012-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK
dc.identifier.scopusauthoridChung, SH=36023203100en_HK
dc.identifier.scopusauthoridChan, LY=7403540482en_HK
dc.identifier.scopusauthoridFinke, G=7004687440en_HK
dc.identifier.scopusauthoridTiwari, MK=35427952100en_HK

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