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Article: Multiobjective evolutionary optimisation for adaptive product family design

TitleMultiobjective evolutionary optimisation for adaptive product family design
Authors
KeywordsEvolutionary algorithm
Mass customisation
Multiobjective optimisation
NSGA-II
Product family design
Product platform
Issue Date2009
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0951192X.asp
Citation
International Journal Of Computer Integrated Manufacturing, 2009, v. 22 n. 4, p. 299-314 How to Cite?
AbstractManufacturing enterprises are under competitive pressure to provide adequate product variety in order to meet diverse customer requirements while striving to reduce cost and time to market by employing product commonality and modularity. One successful approach to mass customisation (MC) is to design a family of product variants simultaneously to strike the optimum balance between commonality and differentiability. This paper formulates product family design as a multiobjective optimisation problem. A new method is proposed for assessing multi-level commonality at the product, module, component and even parameter levels. A multiobjective evolutionary algorithm (MEA) is proposed based on NSGA-II to solve this problem. This method uses a special scheme to represent and track the problem and its solutions. The effectiveness of the approach is first tested through a mathematical problem and then demonstrated with an industrial case of gantry crane family design. Computational experiments show favourable results and benefits of the proposed MEA-based product family design method.
Persistent Identifierhttp://hdl.handle.net/10722/58859
ISSN
2015 Impact Factor: 1.319
2015 SCImago Journal Rankings: 0.673
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Len_HK
dc.contributor.authorHuang, GQen_HK
dc.date.accessioned2010-05-31T03:38:16Z-
dc.date.available2010-05-31T03:38:16Z-
dc.date.issued2009en_HK
dc.identifier.citationInternational Journal Of Computer Integrated Manufacturing, 2009, v. 22 n. 4, p. 299-314en_HK
dc.identifier.issn0951-192Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/58859-
dc.description.abstractManufacturing enterprises are under competitive pressure to provide adequate product variety in order to meet diverse customer requirements while striving to reduce cost and time to market by employing product commonality and modularity. One successful approach to mass customisation (MC) is to design a family of product variants simultaneously to strike the optimum balance between commonality and differentiability. This paper formulates product family design as a multiobjective optimisation problem. A new method is proposed for assessing multi-level commonality at the product, module, component and even parameter levels. A multiobjective evolutionary algorithm (MEA) is proposed based on NSGA-II to solve this problem. This method uses a special scheme to represent and track the problem and its solutions. The effectiveness of the approach is first tested through a mathematical problem and then demonstrated with an industrial case of gantry crane family design. Computational experiments show favourable results and benefits of the proposed MEA-based product family design method.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0951192X.aspen_HK
dc.relation.ispartofInternational Journal of Computer Integrated Manufacturingen_HK
dc.subjectEvolutionary algorithmen_HK
dc.subjectMass customisationen_HK
dc.subjectMultiobjective optimisationen_HK
dc.subjectNSGA-IIen_HK
dc.subjectProduct family designen_HK
dc.subjectProduct platformen_HK
dc.titleMultiobjective evolutionary optimisation for adaptive product family designen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0951-192X&volume=Vol 22, No 4&spage=299&epage=314&date=2008&atitle=Multiobjective+evolutionary+optimisation+for+adaptive+product+family+designen_HK
dc.identifier.emailHuang, GQ:gqhuang@hkucc.hku.hken_HK
dc.identifier.authorityHuang, GQ=rp00118en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/09511920802014920en_HK
dc.identifier.scopuseid_2-s2.0-73349109777en_HK
dc.identifier.hkuros149767en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-73349109777&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume22en_HK
dc.identifier.issue4en_HK
dc.identifier.spage299en_HK
dc.identifier.epage314en_HK
dc.identifier.isiWOS:000264742200003-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLi, L=36064664900en_HK
dc.identifier.scopusauthoridHuang, GQ=7403425048en_HK
dc.identifier.citeulike4290868-

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