Please use this identifier to cite or link to this item: https://doi.org/10.1080/00207540500066812
DC FieldValue
dc.titleModelling a complex supply chain: Understanding the effect of simplified assumptions
dc.contributor.authorHwarng, H.B.
dc.contributor.authorChong, C.S.P.
dc.contributor.authorXie, N.
dc.contributor.authorBurgess, T.F.
dc.date.accessioned2013-10-09T03:25:24Z
dc.date.available2013-10-09T03:25:24Z
dc.date.issued2005
dc.identifier.citationHwarng, H.B., Chong, C.S.P., Xie, N., Burgess, T.F. (2005). Modelling a complex supply chain: Understanding the effect of simplified assumptions. International Journal of Production Research 43 (13) : 2829-2872. ScholarBank@NUS Repository. https://doi.org/10.1080/00207540500066812
dc.identifier.issn00207543
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44043
dc.description.abstractThe benefits of coordinating activities and consolidating distribution points in supply chains are well highlighted and intuitively logical. However, the impact of these decisions on the overall performance of a complex supply chain may not be as obvious as usually perceived. This study models a relatively complex supply chain and evaluates the impact of simplifying demand and lead time assumptions under various supply chain configurations. Of particular interest is the investigation of the effect of risk pooling and the synchronization of production cycles in a multi-level multi-retailer supply chain under the influence of various parameters such as batch size, delivery frequency and ordering cycle. This study highlights the extent of complicated interaction effects among various factors exist in a complex supply chain and shows that that the intricacy of these effects can be better understood with a simulation model. © 2005 Taylor & Francis Group Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/00207540500066812
dc.sourceScopus
dc.subjectInventory
dc.subjectLogistics
dc.subjectSimulation
dc.subjectSupply chain management
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1080/00207540500066812
dc.description.sourcetitleInternational Journal of Production Research
dc.description.volume43
dc.description.issue13
dc.description.page2829-2872
dc.description.codenIJPRB
dc.identifier.isiut000229550100010
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