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Optimal Inventory Policies when the Demand Distribution is not Known
Author:
Erik W. Larsonnull

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,
Mr. Sunil Sharma
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Mr. Lars J. Olsonnull

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Series:
IMF Working Papers
Volume/Issue:
Volume 2000: Issue 183
Language:
English
Publication Date:
01 Nov 2000
DOI:
https://doi.org/10.5089/9781451859300.001
ISBN:
9781451859300
ISSN:
1018-5941
Pages:
24
Keywords:
WP; distribution function
Legal-disclaimer:
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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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.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund
Volume 2000: Issue 183