Constrained Markovian decision processes: the dynamic programming approach

被引：27
|
作者：
Piunovskiy, AB
Mao, X
机构：
[1] Univ Liverpool, Dept Math Sci, Div Stat & Operat Res, Liverpool L69 7ZL, Merseyside, England
[2] Univ Strathclyde, Glasgow, Lanark, Scotland
来源：
OPERATIONS RESEARCH LETTERS | 2000年 / 27卷 / 03期
关键词：
Markovian decision processes; constrained optimization; dynamic programming; penalty functions;
D O I：
10.1016/S0167-6377(00)00039-0
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：
We consider semicontinuous controlled Markov models in discrete time with total expected losses. Only control strategies which meet a set of given constraint inequalities are admissible. One has to build an optimal admissible strategy. The main result consists in the constructive development of optimal strategy with the help of the dynamic programming method. The model studied covers the case of a finite horizon and the case of a homogeneous discounted model with different discount factors. (C) 2000 Elsevier Science B,V. All rights reserved.
引用
收藏
页码：119 / 126
页数：8
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