The Power Approximation for Computing (S, S) Inventory Policies
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Richard A. Ehrhardt, Professor (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: In this paper we present a new analytic approximation for computing (s, S) policies for
single items under periodic review with a set-up cost, linear holding and shortage costs, fixed
replenishment lead time, and backlogging of unfilled demand. The approximation formulae
are derived by using existing results of asymptotic renewal theory to characterize the behavior of the optimal policy numbers as functions of the model parameters. These functions are then used to construct regressions with coefficients that are calibrated by using a grid of 288
known optimal policies as data. The resulting Power Approximation policies (formulae) are
easy to compute and require for demand information only the mean and variance of demand
over lead time. Extensive computational results show that the approximations yield expected
total costs that typically are well within one percent of optimal. The approximation's
robustness is exemplified by analyzing its performance when statistical estimates are used in
place of the actual mean and variance of demand.
The Power Approximation for Computing (S, S) Inventory Policies
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Created on 9/8/2010
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Additional Information
- Publication
- Management Science Vol. 25, No. 8, August 1979 Printed in U.S.A.
- Language: English
- Date: 1979
- Keywords
- (s,S), Inventory management, Production estimates