Dynamic Programming Approximations for a Stochastic Inventory Routing Problem

Anton J. Kleywegt (), Vijay S. Nori and Martin W. P. Savelsbergh ()
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Anton J. Kleywegt: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205
Vijay S. Nori: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205
Martin W. P. Savelsbergh: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205

Transportation Science, 2004, vol. 38, issue 1, 42-70

Abstract: This work is motivated by the need to solve the inventory routing problem when implementing a business practice called vendor managed inventory replenishment (VMI). With VMI, vendors monitor their customers′ inventories and decide when and how much inventory should be replenished at each customer. The inventory routing problem attempts to coordinate inventory replenishment and transportation in such a way that the cost is minimized over the long run. We formulate a Markov decision process model of the stochastic inventory routing problem and propose approximation methods to find good solutions with reasonable computational effort. We indicate how the proposed approach can be used for other Markov decision processes involving the control of multiple resources.

Keywords: freight transportation; logistics; stochastic inventory routing (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (56)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:38:y:2004:i:1:p:42-70

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