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Article: Multicriterion genetic optimization for due date assigned distribution network problems

TitleMulticriterion genetic optimization for due date assigned distribution network problems
Authors
KeywordsAnalytic hierarchy process
Distribution network
Due date
Genetic algorithms
Production scheduling
Issue Date2005
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/dss
Citation
Decision Support Systems, 2005, v. 39 n. 4, p. 661-675 How to Cite?
AbstractThis paper focuses on the demand due date factor in multiechelon distribution network problems and its impact on the production scheduling in manufacturing plants. A reliable demand due date is critical in winning of customer orders. However, this may usually require high collaboration among entities in the network. Mismatching of one single schedule may seriously influence the reliability. In this connection, holistically optimizing the schedule of each entity among the network is essential. In addition, on time delivery may induce high operating cost. A trade-off between earliness, on time, and tardiness should also be considered. Hence, a multicriterion genetic optimization methodology is developed to holistically optimize them. It determines the optimized schedule to collaborate each entity to fulfill the demands. For enabling multicriterion decision-making, the proposed algorithm combines analytic hierarchy process with genetic algorithms (GAs). The problem is divided into two parts - (i) demand allocation and transportation problem, and (ii) production scheduling problem. The optimization approach is applied to iteratively optimize part (i), and then part (ii). Three experiments have been carried out, and the computation results show that the effect of due date is critical, and the ability of the proposed algorithms in taking trade-off between earliness and tardiness. © 2004 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74347
ISSN
2023 Impact Factor: 6.7
2023 SCImago Journal Rankings: 2.211
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorChung, SHen_HK
dc.date.accessioned2010-09-06T07:00:26Z-
dc.date.available2010-09-06T07:00:26Z-
dc.date.issued2005en_HK
dc.identifier.citationDecision Support Systems, 2005, v. 39 n. 4, p. 661-675en_HK
dc.identifier.issn0167-9236en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74347-
dc.description.abstractThis paper focuses on the demand due date factor in multiechelon distribution network problems and its impact on the production scheduling in manufacturing plants. A reliable demand due date is critical in winning of customer orders. However, this may usually require high collaboration among entities in the network. Mismatching of one single schedule may seriously influence the reliability. In this connection, holistically optimizing the schedule of each entity among the network is essential. In addition, on time delivery may induce high operating cost. A trade-off between earliness, on time, and tardiness should also be considered. Hence, a multicriterion genetic optimization methodology is developed to holistically optimize them. It determines the optimized schedule to collaborate each entity to fulfill the demands. For enabling multicriterion decision-making, the proposed algorithm combines analytic hierarchy process with genetic algorithms (GAs). The problem is divided into two parts - (i) demand allocation and transportation problem, and (ii) production scheduling problem. The optimization approach is applied to iteratively optimize part (i), and then part (ii). Three experiments have been carried out, and the computation results show that the effect of due date is critical, and the ability of the proposed algorithms in taking trade-off between earliness and tardiness. © 2004 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/dssen_HK
dc.relation.ispartofDecision Support Systemsen_HK
dc.rightsDecision Support Systems. Copyright © Elsevier BV.en_HK
dc.subjectAnalytic hierarchy processen_HK
dc.subjectDistribution networken_HK
dc.subjectDue dateen_HK
dc.subjectGenetic algorithmsen_HK
dc.subjectProduction schedulingen_HK
dc.titleMulticriterion genetic optimization for due date assigned distribution network problemsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0167-9236&volume=39&spage=661&epage=675&date=2005&atitle=Multicriterion+genetic+optimisation+for+due+date+assigned+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.doi10.1016/j.dss.2004.03.004en_HK
dc.identifier.scopuseid_2-s2.0-11244309098en_HK
dc.identifier.hkuros100481en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-11244309098&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume39en_HK
dc.identifier.issue4en_HK
dc.identifier.spage661en_HK
dc.identifier.epage675en_HK
dc.identifier.isiWOS:000229049400008-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK
dc.identifier.scopusauthoridChung, SH=36023203100en_HK
dc.identifier.issnl0167-9236-

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