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Article: Application of genetic algorithms with dominant genes in a distributed scheduling problem in flexible manufacturing systems

TitleApplication of genetic algorithms with dominant genes in a distributed scheduling problem in flexible manufacturing systems
Authors
KeywordsDistributed scheduling
Dominant genes
Flexible manufacturing systems (FMS)
Genetic algorithms
Issue Date2006
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.asp
Citation
International Journal Of Production Research, 2006, v. 44 n. 3, p. 523-543 How to Cite?
AbstractMulti-factory production networks have increased in recent years. With the factories located in different geographic areas, companies can benefit from various advantages, such as closeness to their customers, and can respond faster to market changes. Products (jobs) in the network can usually be produced in more than one factory. However, each factory has its operations efficiency, capacity, and utilization level. Allocation of jobs inappropriately in a factory will produce high cost, long lead time, overloading or idling resources, etc. This makes distributed scheduling more complicated than classical production scheduling problems because it has to determine how to allocate the jobs into suitable factories, and simultaneously determine the production scheduling in each factory as well. The problem is even more complicated when alternative production routing is allowed in the factories. This paper proposed a genetic algorithm with dominant genes to deal with distributed scheduling problems, especially in a flexible manufacturing system (FMS) environment. The idea of dominant genes is to identify and record the critical genes in the chromosome and to enhance the performance of genetic search. To testify and benchmark the optimization reliability, the proposed algorithm has been compared with other approaches on several distributed scheduling problems. These comparisons demonstrate the importance of distributed scheduling and indicate the optimization reliability of the proposed algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/74455
ISSN
2015 Impact Factor: 1.693
2015 SCImago Journal Rankings: 1.445
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorChung, SHen_HK
dc.contributor.authorChan, PLYen_HK
dc.date.accessioned2010-09-06T07:01:30Z-
dc.date.available2010-09-06T07:01:30Z-
dc.date.issued2006en_HK
dc.identifier.citationInternational Journal Of Production Research, 2006, v. 44 n. 3, p. 523-543en_HK
dc.identifier.issn0020-7543en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74455-
dc.description.abstractMulti-factory production networks have increased in recent years. With the factories located in different geographic areas, companies can benefit from various advantages, such as closeness to their customers, and can respond faster to market changes. Products (jobs) in the network can usually be produced in more than one factory. However, each factory has its operations efficiency, capacity, and utilization level. Allocation of jobs inappropriately in a factory will produce high cost, long lead time, overloading or idling resources, etc. This makes distributed scheduling more complicated than classical production scheduling problems because it has to determine how to allocate the jobs into suitable factories, and simultaneously determine the production scheduling in each factory as well. The problem is even more complicated when alternative production routing is allowed in the factories. This paper proposed a genetic algorithm with dominant genes to deal with distributed scheduling problems, especially in a flexible manufacturing system (FMS) environment. The idea of dominant genes is to identify and record the critical genes in the chromosome and to enhance the performance of genetic search. To testify and benchmark the optimization reliability, the proposed algorithm has been compared with other approaches on several distributed scheduling problems. These comparisons demonstrate the importance of distributed scheduling and indicate the optimization reliability of the proposed algorithm.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.aspen_HK
dc.relation.ispartofInternational Journal of Production Researchen_HK
dc.subjectDistributed schedulingen_HK
dc.subjectDominant genesen_HK
dc.subjectFlexible manufacturing systems (FMS)en_HK
dc.subjectGenetic algorithmsen_HK
dc.titleApplication of genetic algorithms with dominant genes in a distributed scheduling problem in flexible manufacturing systemsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0020-7543&volume=44&issue=3&spage=523&epage=543&date=2006&atitle=Application+of+genetic+algorithms+with+dominant+genes+in+a+distributed+scheduling+problem+in+flexible+manufacturing+systemsen_HK
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hken_HK
dc.identifier.emailChan, PLY: plychan@hku.hken_HK
dc.identifier.authorityChan, FTS=rp00090en_HK
dc.identifier.authorityChan, PLY=rp00093en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/00207540500319229en_HK
dc.identifier.scopuseid_2-s2.0-30844449000en_HK
dc.identifier.hkuros119202en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-30844449000&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume44en_HK
dc.identifier.issue3en_HK
dc.identifier.spage523en_HK
dc.identifier.epage543en_HK
dc.identifier.isiWOS:000234584000006-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK
dc.identifier.scopusauthoridChung, SH=36023203100en_HK
dc.identifier.scopusauthoridChan, PLY=7403540482en_HK

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