Discounted stochastic fluid programs
成果类型：
Article
署名作者：
Bäuerle, N
署名单位：
Ulm University
刊物名称：
MATHEMATICS OF OPERATIONS RESEARCH
ISSN/ISSBN：
0364-765X
DOI：
10.1287/moor.26.2.401.10560
发表日期：
2001
页码：
401-420
关键词：
摘要：
We consider optimal control problems for stochastic fluid models of the following type: Suppose (Z(t)) is a continuous-time Markov chain with finite state space. As long as Z(t) = z, the dynamics of the system at rime t are given by a function b(2)(u((.))), where u is a control we have to choose. A cost rate function c is given, depending on the state and the action. We want to control the system in such a way as to minimize the expected discounted cost over an infinite horizon. We will call a problem of this type a Stochastic Fluid Program (SFP). They typically appear in production and telecommunication systems. We formulate the optimization problem as a discrete time Markov decision process and give conditions under which an optimal stationary policy exists. Furthermore, we show how to solve SFPs numerically, using Kushner's approximating Markov chain approach. Last but not least, we apply our results to a multiproduct manufacturing system without backlog.
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