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Optimal policy for a dynamic multi‐echelon inventory model

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  • Stuart A. Bessler
  • Arthur F. Veinott

Abstract

A general multiperiod multi‐echelon supply system consisting of n facilities each stocking a single product is studied. At the beginning of a period each facility may order stock from an exogenous source with no delivery lag and proportional ordering costs. During the period the (random) demands at the facilities are satisfied according to a given supply policy that determines to what extent stock may be redistributed from facilities with excess stock to those experiencing shortages. There are storage, shortage, and transportation costs. An ordering policy that minimizes expected costs is sought. If the initial stock is sufficiently small and certain other conditions are fulfilled, it is optimal to order up to a certain base stock level at each facility. The special supply policy in which each facility except facility 1 passes its shortages on to a given lower numbered facility called its direct supplier is examined in some detail. Bounds on the base stock levels are obtained. It is also shown that if the demand distribution at facility j is stochastically smaller (“spread” less) than that at another facility k having the same direct supplier and if certain other conditions are fulfilled, then the optimal base stock level (“virtual” stock out probability) at j is less than (greater than) or equal to that at facility k.

Suggested Citation

  • Stuart A. Bessler & Arthur F. Veinott, 1966. "Optimal policy for a dynamic multi‐echelon inventory model," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 13(4), pages 355-389, December.
  • Handle: RePEc:wly:navlog:v:13:y:1966:i:4:p:355-389
    DOI: 10.1002/nav.3800130402
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    Cited by:

    1. Bulinskaya, E. V., 2004. "Stochastic orders and inventory problems," International Journal of Production Economics, Elsevier, vol. 88(2), pages 125-135, March.
    2. Arthur Veinott, 2013. "Taut-string solution of the equilibrium no-lag Clark-Scarf serial inventory problem," Annals of Operations Research, Springer, vol. 208(1), pages 27-30, September.

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