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Article: An adaptive genetic algorithm for manufacturing cell formation

TitleAn adaptive genetic algorithm for manufacturing cell formation
Authors
Issue Date2000
PublisherSpringer U K. The Journal's web site is located at http://www.springer.com/engineering/production+eng/journal/170
Citation
International Journal Of Advanced Manufacturing Technology, 2000, v. 16 n. 7, p. 491-497 How to Cite?
AbstractAn adaptive genetic approach is proposed as an effective means of providing the optimal solution to the manufacturing cell formation problem in the design of cellular manufacturing systems. The proposed approach generates the optimal formation of machine cells and part families by sequencing the rows and columns of a machine-part incidence matrix, so as to maximize the bond energy of the incidence matrix. In order to enhance the performance of the genetic search process, an adaptive scheme is adopted, so that the genetic parameters can be adjusted during the genetic search process. The effectiveness of the proposed approach is demonstrated by applying it to two numerical examples and 11 benchmark problems obtained from the literature. The computational results show that the proposed approach provides a powerful but simple means of solving the manufacturing cell formation problem and thus facilitates the design of cellular manufacturing systems.
Persistent Identifierhttp://hdl.handle.net/10722/155839
ISSN
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.696
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_US
dc.contributor.authorWong, YSen_US
dc.contributor.authorWang, XXen_US
dc.date.accessioned2012-08-08T08:37:58Z-
dc.date.available2012-08-08T08:37:58Z-
dc.date.issued2000en_US
dc.identifier.citationInternational Journal Of Advanced Manufacturing Technology, 2000, v. 16 n. 7, p. 491-497en_US
dc.identifier.issn0268-3768en_US
dc.identifier.urihttp://hdl.handle.net/10722/155839-
dc.description.abstractAn adaptive genetic approach is proposed as an effective means of providing the optimal solution to the manufacturing cell formation problem in the design of cellular manufacturing systems. The proposed approach generates the optimal formation of machine cells and part families by sequencing the rows and columns of a machine-part incidence matrix, so as to maximize the bond energy of the incidence matrix. In order to enhance the performance of the genetic search process, an adaptive scheme is adopted, so that the genetic parameters can be adjusted during the genetic search process. The effectiveness of the proposed approach is demonstrated by applying it to two numerical examples and 11 benchmark problems obtained from the literature. The computational results show that the proposed approach provides a powerful but simple means of solving the manufacturing cell formation problem and thus facilitates the design of cellular manufacturing systems.en_US
dc.languageengen_US
dc.publisherSpringer U K. The Journal's web site is located at http://www.springer.com/engineering/production+eng/journal/170en_US
dc.relation.ispartofInternational Journal of Advanced Manufacturing Technologyen_US
dc.titleAn adaptive genetic algorithm for manufacturing cell formationen_US
dc.typeArticleen_US
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_US
dc.identifier.authorityMak, KL=rp00154en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s001700070057en_US
dc.identifier.scopuseid_2-s2.0-0033690389en_US
dc.identifier.hkuros55243-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0033690389&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume16en_US
dc.identifier.issue7en_US
dc.identifier.spage491en_US
dc.identifier.epage497en_US
dc.identifier.isiWOS:000088038700005-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridMak, KL=7102680226en_US
dc.identifier.scopusauthoridWong, YS=26637607500en_US
dc.identifier.scopusauthoridWang, XX=9246057600en_US
dc.identifier.issnl0268-3768-

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