A model for integrating shipment consolidation and pricing decisions in perishable product supply chains

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dc.contributorInternational FAIM Conference 24th : 2014 : San Antonio, Texas
dc.contributorUniversity of Texas at San Antonio. Center for Advanced Manufacturing and Lean Systems
dc.contributor.authorChen, Jing
dc.contributor.authorDong, Ming, Ph. D.
dc.contributor.authorChen, F. Frank
dc.date.accessioned2022-07-11T17:35:31Z
dc.date.available2022-07-11T17:35:31Z
dc.date.issued2014
dc.descriptionPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio
dc.descriptionIncludes bibliographical references
dc.description.abstractThis paper focuses on a simple perishable product supply chain with a vendor and multiple retailers. These retailers, densely dispersed in a distribution zone, are sensitive to price, delivery time and product quality. With the aim of optimizing vendor's average expected profit during a shipment consolidation cycle, an analytical model is proposed for this problem. The upper unbound expressions of optimal time policy and fresh-keeping cost are given based on a certain range of time parameter. Then our theoretical findings are verified by using a numerical case. Some useful managerial insights are obtained based on analyzing the sensitivity of this model on major parameters.
dc.identifier.otherhttp://dx.doi.org/10.14809/faim.2014.0435
dc.identifier.urihttps://hdl.handle.net/20.500.12588/982
dc.language.isoen_US
dc.publisherDEStech Publications, Inc.
dc.relation.ispartofseriesProceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing
dc.subjectFarm produce--Transportation
dc.subjectFarm produce--Marketing
dc.subjectBusiness logistics
dc.subjectMathematical optimization
dc.titleA model for integrating shipment consolidation and pricing decisions in perishable product supply chains
dc.typeArticle

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