Inventory models with Markovian demands and cost functions of polynomial growth

被引:35
作者
Beyer, D [1 ]
Sethi, SP
Taksar, M
机构
[1] Hewlett Packard Labs, Palo Alto, CA 94304 USA
[2] Univ Texas, Sch Management, Richardson, TX USA
[3] SUNY Stony Brook, Dept Appl Math, Stony Brook, NY 11794 USA
基金
加拿大自然科学与工程研究理事会; 美国国家科学基金会;
关键词
dynamic inventory models; Markov chains; dynamic programming; finite horizon; infinite horizon; cyclic demand; (s; S)-policy;
D O I
10.1023/A:1022633400174
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 studies stochastic inventory problems with unbounded Markovian demands, ordering costs that are lower semicontinuous, and inventory/backlog (or surplus) costs that are lower semicontinuous with polynomial growth. Finite-horizon problems, stationary and nonstationary discounted-cost infinite-horizon problems, and stationary long-run average-cost problems are addressed. Existence of optimal Markov or feedback policies is established. Furthermore, optimality of (s, S)-type policies is proved when, in addition, the ordering cost consists of fixed and proportional cost components and the surplus cost is convex.
引用
收藏
页码:281 / 323
页数:43
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