Using stochastic approximation methods to compute optimal base-stock levels in inventory control problems
成果类型：
Article
署名作者：
Kunnumkal, Sumit; Topaloglu, Huseyin
署名单位：
Indian School of Business (ISB); Cornell University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1070.0477
发表日期：
2008
页码：
646-664
关键词：
摘要：
In this paper, we consider numerous inventory control problems for which the base-stock policies are known to be optimal, and we propose stochastic approximation methods to compute the optimal base-stock levels. The existing stochastic approximation methods in the literature guarantee that their iterates converge, but not necessarily to the optimal base-stock levels. In contrast, we prove that the iterates of our methods converge to the optimal base-stock levels. Moreover, our methods continue to enjoy the well-known advantages of the existing stochastic approximation methods. In particular, they only require the ability to obtain samples of the demand random variables, rather than to compute expectations explicitly, and they are applicable even when the demand information is censored by the amount of available inventory.