Journal
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume 48, Issue 1, Pages 310-330Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2011.08.006
Keywords
Markov decision processes; Cold supply chain; Perishable freight transportation
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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. (C) 2011 Elsevier Ltd. All rights reserved.
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