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Article: Multi-criteria genetic optimization for distribution network problems

TitleMulti-criteria genetic optimization for distribution network problems
Authors
KeywordsAnalytic hierarchy process
Distribution network
Genetic algorithms
Linear programming
Multi-criterion decision-making
Issue Date2004
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, 2004, v. 24 n. 7-8, p. 517-532 How to Cite?
AbstractThis paper develops a multi-criterion genetic optimization for solving distribution network problems in supply chain management. Distribution problems deal with distribution from a number of sources to a number of destinations, in which various decision factors are closely related and influence each other. Genetic algorithms have been widely adopted as the optimization tool in solving these problems. This paper combines analytic hierarchy processes with genetic algorithms to capture the capability of multi-criterion decision-making. The proposed algorithm allows decision-makers to give weightings for criteria using a pairwise comparison approach. The numerical results obtained from the new approach are compared with the results obtained from linear programming. The result shows that the proposed algorithm is reliable and robust. In addition, it provides more control for decision-makers on the determination of the optimization solutions, and gains more information for a better insight into the distribution network. © Springer-Verlag London Limited 2004.
Persistent Identifierhttp://hdl.handle.net/10722/74265
ISSN
2015 Impact Factor: 1.568
2015 SCImago Journal Rankings: 0.915
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorChung, SHen_HK
dc.date.accessioned2010-09-06T06:59:35Z-
dc.date.available2010-09-06T06:59:35Z-
dc.date.issued2004en_HK
dc.identifier.citationInternational Journal Of Advanced Manufacturing Technology, 2004, v. 24 n. 7-8, p. 517-532en_HK
dc.identifier.issn0268-3768en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74265-
dc.description.abstractThis paper develops a multi-criterion genetic optimization for solving distribution network problems in supply chain management. Distribution problems deal with distribution from a number of sources to a number of destinations, in which various decision factors are closely related and influence each other. Genetic algorithms have been widely adopted as the optimization tool in solving these problems. This paper combines analytic hierarchy processes with genetic algorithms to capture the capability of multi-criterion decision-making. The proposed algorithm allows decision-makers to give weightings for criteria using a pairwise comparison approach. The numerical results obtained from the new approach are compared with the results obtained from linear programming. The result shows that the proposed algorithm is reliable and robust. In addition, it provides more control for decision-makers on the determination of the optimization solutions, and gains more information for a better insight into the distribution network. © Springer-Verlag London Limited 2004.en_HK
dc.languageengen_HK
dc.publisherSpringer U K. The Journal's web site is located at http://www.springer.com/engineering/production+eng/journal/170en_HK
dc.relation.ispartofInternational Journal of Advanced Manufacturing Technologyen_HK
dc.subjectAnalytic hierarchy processen_HK
dc.subjectDistribution networken_HK
dc.subjectGenetic algorithmsen_HK
dc.subjectLinear programmingen_HK
dc.subjectMulti-criterion decision-makingen_HK
dc.titleMulti-criteria genetic optimization for distribution network problemsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0268-3768&volume=24&spage=517&epage=532&date=2004&atitle=Multi-criteria+genetic+optimisation+for+distribution+network+problemsen_HK
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hken_HK
dc.identifier.authorityChan, FTS=rp00090en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s00170-002-1445-5en_HK
dc.identifier.scopuseid_2-s2.0-33646223540en_HK
dc.identifier.hkuros100450en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33646223540&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume24en_HK
dc.identifier.issue7-8en_HK
dc.identifier.spage517en_HK
dc.identifier.epage532en_HK
dc.identifier.isiWOS:000224895700008-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK
dc.identifier.scopusauthoridChung, SH=36023203100en_HK
dc.identifier.citeulike6567359-

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