In-transit perishable product inspection

Chelsea C. White; Taesu Cheong

doi:10.1016/j.tre.2011.08.006

In-transit perishable product inspection

Chelsea C. White, Taesu Cheong

Research output: Contribution to journal › Article › peer-review

25 Citations (Scopus)

Abstract

We determine the value of monitoring perishable freight in-transit for a single vehicle traveling from an origin to a destination. We develop a computationally practical approach for determining the optimal expected cost function and an optimal policy, based on an infinite horizon partially observed Markov decision process model. Structural properties of the optimal expected cost function and optimal policy are determined. These results can lend insight when deciding whether to acquire the capacity to monitor freight status in transit and what actions to take, based on the data from the in-transit monitoring, that optimally increase expected supply chain productivity.

Original language	English
Pages (from-to)	310-330
Number of pages	21
Journal	Transportation Research Part E: Logistics and Transportation Review
Volume	48
Issue number	1
DOIs	https://doi.org/10.1016/j.tre.2011.08.006
Publication status	Published - 2012 Jan
Externally published	Yes

Keywords

Cold supply chain
Markov decision processes
Perishable freight transportation

ASJC Scopus subject areas

Business and International Management
Civil and Structural Engineering
Transportation

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10.1016/j.tre.2011.08.006

Cite this

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title = "In-transit perishable product inspection",

abstract = "We determine the value of monitoring perishable freight in-transit for a single vehicle traveling from an origin to a destination. We develop a computationally practical approach for determining the optimal expected cost function and an optimal policy, based on an infinite horizon partially observed Markov decision process model. Structural properties of the optimal expected cost function and optimal policy are determined. These results can lend insight when deciding whether to acquire the capacity to monitor freight status in transit and what actions to take, based on the data from the in-transit monitoring, that optimally increase expected supply chain productivity.",

keywords = "Cold supply chain, Markov decision processes, Perishable freight transportation",

author = "White, {Chelsea C.} and Taesu Cheong",

note = "Funding Information: This research was partially supported by the Sloan Foundation Industry Study Program. This research was also partially supported by the US Department of Homeland Security (Grant No. N-00014-04-1-0659), through a grant awarded to the National Center for Food Protection and Defense at the University of Minnesota. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not represent the policy or position of either the Sloan Foundation or the Department of Homeland Security. The authors would like to thank two anonymous reviewers for their constructive comments and suggestions, which helped to improve the quality and clarity of this paper. ",

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KW - Markov decision processes

KW - Perishable freight transportation

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ER -

In-transit perishable product inspection

Abstract

Keywords

ASJC Scopus subject areas

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