Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22312
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorTse, YK-
dc.creatorTan, KH-
dc.creatorTing, SL-
dc.creatorChoy, KL-
dc.creatorHo, GTS-
dc.creatorChung, SH-
dc.date.accessioned2015-06-23T09:09:55Z-
dc.date.available2015-06-23T09:09:55Z-
dc.identifier.issn0020-7543-
dc.identifier.urihttp://hdl.handle.net/10397/22312-
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subject3PLen_US
dc.subjectintelligent systemsen_US
dc.subjectpicks and pack operationen_US
dc.subjectpostponementen_US
dc.titleImproving postponement operation in warehouse : an intelligent pick-and-pack decision-support systemen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage7181-
dc.identifier.epage7197-
dc.identifier.volume50-
dc.identifier.issue24-
dc.identifier.doi10.1080/00207543.2011.643505-
dcterms.abstractToday, many manufacturers prefer to shift their pick-and-pack postponement operations to third-party logistics companies to lower operational cost and improve mass customisation flexibility. The type of pick-and-pack operation is complicated, as it usually involves a large number of stock keeping units and several warehouse operations. Surprisingly, in most 3PL, the complicated postponement operations are still mainly managed by an experienced warehouse manager, which is an unreliable methodology and often creates many mistakes. A hybrid intelligent system integrating Case-Based Reasoning and Fuzzy Logic is proposed to support the manager in making pick-and-pack postponement decisions. The system comprises a solution-refining module that proposes and holds the details of past pick-and-pack operations. This approach will be of benefit to managers as effective decision support of pick and pack planning can be provided. A case study is used to illustrate the applicability and effectiveness of the approach. Implications of the proposed approach are discussed, and suggestions for further work are outlined.-
dcterms.bibliographicCitationInternational journal of production research, 2012, v. 50, no. 24, p. 7181-7197-
dcterms.isPartOfInternational journal of production research-
dcterms.issued2012-
dc.identifier.isiWOS:000310604200008-
dc.identifier.scopus2-s2.0-84868705175-
dc.identifier.eissn1366-588X-
dc.identifier.rosgroupidr62367-
dc.description.ros2012-2013 > Academic research: refereed > Publication in refereed journal-
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