Average cost optimality in inventory models with Markovian demands

被引:38
作者
Beyer, D
Sethi, SP
机构
[1] Faculty of Management, University of Toronto, Toronto, Ont.
基金
加拿大自然科学与工程研究理事会;
关键词
dynamic inventory model; Markov chain; dynamic programming; infinite horizon; long-run average cost; ergodic cost; (s; S); policy;
D O I
10.1023/A:1022651322174
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper is concerned with long-run average cost minimization of a stochastic inventory problem with Markovian demand, fixed ordering cost, and convex surplus cost. The states of the Markov chain represent different possible states of the environment. Using a vanishing discount approach, a dynamic programming equation and the corresponding verification theorem are established. Finally, the existence of an optimal state-dependent (s, S) policy is proved.
引用
收藏
页码:497 / 526
页数:30
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