Probabilistic Analyses and Practical Algorithms for Inventory-Routing Models

Lap Mui Ann Chan, Awi Federgruen and David Simchi-Levi
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Lap Mui Ann Chan: Philips Laboratories, Briarcliff Manor, New York
Awi Federgruen: Columbia University, New York
David Simchi-Levi: Northwestern University, Evanston, Illinois

Operations Research, 1998, vol. 46, issue 1, 96-106

Abstract: We consider a distribution system consisting of a single warehouse and many geographically dispersed retailers. Each retailer faces demands for a single item which arise at a deterministic, retailer specific rate. The retailers' stock is replenished by a fleet of vehicles of limited capacity, departing and returning to the warehouse and combining deliveries into efficient routes. The cost of any given route consists of a fixed component and a component which is proportional with the total distance driven. Inventory costs are proportional with the stock levels. The objective is to identify a combined inventory policy and a routing strategy minimizing system-wide infinite horizon costs. We characterize the asymptotic effectiveness of the class of so-called Fixed Partition policies and those employing Zero Inventory Ordering. We provide worst case as well as probabilistic bounds under a variety of probabilistic assumptions. This insight is used to construct a very effective algorithm resulting in a Fixed Partition policy which is asymptotically optimal within its class. Computational results show that the algorithm is very effective on a set of randomly generated problems.

Keywords: Transportation; Vehicle routing; Inventory/production; multiechelon (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (29)

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