UID:
edocfu_9958124434202883
Format:
1 online resource (24 pages)
ISBN:
1-4623-3068-1
,
1-4527-7944-9
,
1-282-10672-4
,
1-4519-0466-5
,
9786613800077
Series Statement:
IMF Working Papers
Content:
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.
Note:
Bibliographic Level Mode of Issuance: Monograph
,
English
Additional Edition:
ISBN 1-4518-5930-9
Language:
English
