Average cost per unit time control of stochastic manufacturing systems: Revisited

被引：0
|
作者：
T. E. Duncan
B. Pasik-Duncan
Ł. Stettner
机构：
[1] Department of Mathematics,
[2] University of Kansas,undefined
[3] Lawrence,undefined
[4] KS 66045,undefined
[5] U.S.A.,undefined
[6] duncan@math.ukans.edu,undefined
[7] bozenna@math.ukans.edu,undefined
[8] Institute of Mathematics,undefined
[9] Polish Academy of Sciences,undefined
[10] Sniadeckich 8,undefined
[11] 00-950 Warsaw,undefined
[12] Poland,undefined
[13] stettner@impan.gov.pl.,undefined
来源：
Mathematical Methods of Operations Research | 2001年 / 54卷
关键词：
Key words: dynamic programming; stochastic manufacturing systems; large deviations; average cost per unit time;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An optimal production planning for a stochastic manufacturing system is considered. The system consists of a single, failure-prone machine that produces a finite number of different products. The objective is to determine a rate of production that minimizes an average cost per unit time criterion where the demand is random. The results given in this paper are based on some large deviation estimates and the Hamilton-Jacobi-Bellman equations for convex functions.
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页码：259 / 278
页数：19
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