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Article: An adaptive genetic algorithm with dominated genes for distributed scheduling problems

TitleAn adaptive genetic algorithm with dominated genes for distributed scheduling problems
Authors
KeywordsAdaptive genetic algorithm
Dominated genes
Scheduling problems
Issue Date2005
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa
Citation
Expert Systems With Applications, 2005, v. 29 n. 2, p. 364-371 How to Cite?
AbstractThis paper proposes an adaptive genetic algorithm for distributed scheduling problems in multi-factory and multi-product environment. Distributed production strategy enables factories to be more focused on their core product types, to achieve better quality, to reduce production cost, and to reduce management risk. However, when comparing with single-factory production, scheduling problems involved in multi-factory one are more complicated, since different jobs distributed to different factories will have different production scheduling, consequently affect the performance of the supply chain. Distributed scheduling problems deal with the assignment of jobs to suitable factories and determine their production scheduling accordingly. In this paper, a new crossover mechanism named dominated gene crossover will be introduced to enhance the performance of genetic search, and eliminate the problem of determining optimal crossover rate. A number of experiments have been carried out. For the comparison purpose, five multi-factory models have been solved by different well known optimization approaches. The results indicate that significant improvement could be obtained by the proposed algorithm. © 2005 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74435
ISSN
2015 Impact Factor: 2.981
2015 SCImago Journal Rankings: 1.839
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorChung, SHen_HK
dc.contributor.authorChan, PLYen_HK
dc.date.accessioned2010-09-06T07:01:18Z-
dc.date.available2010-09-06T07:01:18Z-
dc.date.issued2005en_HK
dc.identifier.citationExpert Systems With Applications, 2005, v. 29 n. 2, p. 364-371en_HK
dc.identifier.issn0957-4174en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74435-
dc.description.abstractThis paper proposes an adaptive genetic algorithm for distributed scheduling problems in multi-factory and multi-product environment. Distributed production strategy enables factories to be more focused on their core product types, to achieve better quality, to reduce production cost, and to reduce management risk. However, when comparing with single-factory production, scheduling problems involved in multi-factory one are more complicated, since different jobs distributed to different factories will have different production scheduling, consequently affect the performance of the supply chain. Distributed scheduling problems deal with the assignment of jobs to suitable factories and determine their production scheduling accordingly. In this paper, a new crossover mechanism named dominated gene crossover will be introduced to enhance the performance of genetic search, and eliminate the problem of determining optimal crossover rate. A number of experiments have been carried out. For the comparison purpose, five multi-factory models have been solved by different well known optimization approaches. The results indicate that significant improvement could be obtained by the proposed algorithm. © 2005 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/eswaen_HK
dc.relation.ispartofExpert Systems with Applicationsen_HK
dc.subjectAdaptive genetic algorithmen_HK
dc.subjectDominated genesen_HK
dc.subjectScheduling problemsen_HK
dc.titleAn adaptive genetic algorithm with dominated genes for distributed scheduling problemsen_HK
dc.typeArticleen_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.doi10.1016/j.eswa.2005.04.009en_HK
dc.identifier.scopuseid_2-s2.0-22144475484en_HK
dc.identifier.hkuros100314en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-22144475484&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume29en_HK
dc.identifier.issue2en_HK
dc.identifier.spage364en_HK
dc.identifier.epage371en_HK
dc.identifier.isiWOS:000230947400013-
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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