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Article: Fuzzy chance-constrained programming model for a multi-echelon reverse logistics network for household appliances

TitleFuzzy chance-constrained programming model for a multi-echelon reverse logistics network for household appliances
Authors
KeywordsFuzzy-chance constrained programming
Hybrid genetic algorithm
Reverse logistics network
Issue Date2010
PublisherPalgrave Macmillan Ltd. The Journal's web site is located at http://www.palgrave-journals.com/jors/index.html
Citation
Journal Of The Operational Research Society, 2010, v. 61 n. 4, p. 551-560 How to Cite?
AbstractEfficient planning and design of an appropriate reverse logistics network is crucial to the economical collection and disposal of scrapped household appliances and electrical products. Such systems are commonly modelled as mixed-integer programs, whose solutions will determine the location of individual facilities that optimize material flow. One of the major drawbacks of current models is that they do not adequately address the important issue of uncertainty in demand and supply. Another deficiency in current models is that they are restricted to a two-echelon system. This study addresses these deficiencies by embodying such uncertainties in the model using the technique of fuzzy-chance constrained programming, and by extending the model to a three-echelon system. A heuristic in the form of a hybrid genetic algorithm is then employed to generate low-cost solutions. The overall objective is to find economical solutions to the general problem of determining the volume of appliances to be moved between the three echelons of customer base to collection sites, collection sites to disposal centres and disposal centre to landfill centre/remanufacturing centre; and to the problems of positioning the disposal centres and the landfill centre/remanufacturing centres within the problem domain. A case example in China is presented and the quality and robustness of the solutions are explored through sensitivity analysis. © 2010 Operational Research Society Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/58876
ISSN
2015 Impact Factor: 1.225
2015 SCImago Journal Rankings: 1.026
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChu, LKen_HK
dc.contributor.authorShi, Yen_HK
dc.contributor.authorLin, Sen_HK
dc.contributor.authorSculli, Den_HK
dc.contributor.authorNi, Jen_HK
dc.date.accessioned2010-05-31T03:38:36Z-
dc.date.available2010-05-31T03:38:36Z-
dc.date.issued2010en_HK
dc.identifier.citationJournal Of The Operational Research Society, 2010, v. 61 n. 4, p. 551-560en_HK
dc.identifier.issn0160-5682en_HK
dc.identifier.urihttp://hdl.handle.net/10722/58876-
dc.description.abstractEfficient planning and design of an appropriate reverse logistics network is crucial to the economical collection and disposal of scrapped household appliances and electrical products. Such systems are commonly modelled as mixed-integer programs, whose solutions will determine the location of individual facilities that optimize material flow. One of the major drawbacks of current models is that they do not adequately address the important issue of uncertainty in demand and supply. Another deficiency in current models is that they are restricted to a two-echelon system. This study addresses these deficiencies by embodying such uncertainties in the model using the technique of fuzzy-chance constrained programming, and by extending the model to a three-echelon system. A heuristic in the form of a hybrid genetic algorithm is then employed to generate low-cost solutions. The overall objective is to find economical solutions to the general problem of determining the volume of appliances to be moved between the three echelons of customer base to collection sites, collection sites to disposal centres and disposal centre to landfill centre/remanufacturing centre; and to the problems of positioning the disposal centres and the landfill centre/remanufacturing centres within the problem domain. A case example in China is presented and the quality and robustness of the solutions are explored through sensitivity analysis. © 2010 Operational Research Society Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPalgrave Macmillan Ltd. The Journal's web site is located at http://www.palgrave-journals.com/jors/index.htmlen_HK
dc.relation.ispartofJournal of the Operational Research Societyen_HK
dc.rightsJournal of the Operational Research Society. Copyright © Palgrave Macmillan.-
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in Journal of the Operational Research Society. The definitive publisher-authenticated version Journal of the Operational Research Society, 2010, v. 61 n. 4, p. 551–560 is available online at: http://www.palgrave-journals.com/jors/index.html-
dc.subjectFuzzy-chance constrained programmingen_HK
dc.subjectHybrid genetic algorithmen_HK
dc.subjectReverse logistics networken_HK
dc.titleFuzzy chance-constrained programming model for a multi-echelon reverse logistics network for household appliancesen_HK
dc.typeArticleen_HK
dc.identifier.emailChu, LK:lkchu@hkucc.hku.hken_HK
dc.identifier.authorityChu, LK=rp00113en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1057/jors.2008.162en_HK
dc.identifier.scopuseid_2-s2.0-77949448842en_HK
dc.identifier.hkuros162516en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77949448842&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume61en_HK
dc.identifier.issue4en_HK
dc.identifier.spage551en_HK
dc.identifier.epage560en_HK
dc.identifier.eissn1476-9360-
dc.identifier.isiWOS:000275445300002-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChu, LK=7202233520en_HK
dc.identifier.scopusauthoridShi, Y=16508014700en_HK
dc.identifier.scopusauthoridLin, S=23091672900en_HK
dc.identifier.scopusauthoridSculli, D=7003917046en_HK
dc.identifier.scopusauthoridNi, J=35771345200en_HK
dc.identifier.citeulike6852946-

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