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Optimal Inventory Policies when the Demand Distribution is not Known, Erik Larson, Sunil Sharma, Lars Olson

Abstract
This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm’s prior information is characterized by a Dirichlet process prior. This provides considerable freedom in the specification of prior information about demand and it permits the accommodation of fixed order costs. As information on the demand distribution accumulates, optimal history-dependent (s,S) rules are shown to converge to an (s,S) rule that is optimal when the underlying demand distribution is known
Language
eng
Literary Form
non fiction
Note
Bibliographic Level Mode of Issuance: Monograph
Physical Description
1 online resource (24 pages)
Form Of Item
online
Isbn
9781282106727

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