A simple heuristic for computing nonstationary (s, S) policies
成果类型：
Article
署名作者：
Bollapragada, S; Morton, TE
署名单位：
General Electric; Carnegie Mellon University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.47.4.576
发表日期：
1999
页码：
576-584
关键词：
摘要：
Nonstationary inventory problems with set-up costs, proportional ordering costs, and stochastic demands occur in a large number of industrial distribution, and service contexts. It is well known that nonstationary (s, S) policies are optimal for such problems. In this paper, we propose a simple, myopic heuristic for computing the policies. The heuristic involves approximating the future problem at each period by a stationary one and obtaining the solution to the corresponding stationary problem. We numerically compare our heuristic with an earlier myopic heuristic and the optimal dynamic programming solution procedure. Over all problems tested, the new heuristic averaged 1.7% error, compared with 2.0% error for the old procedure, and is on average 399 times as fast as the D.P. and 2062 as fast as the old heuristic. Moreover, our heuristic, awing to its myopic nature, requires the demand data only a few periods into the future, while the dynamic programming solution needs the demand data for the entire time horizon-which are typically not available in most practical situations.