Markov decision chains with unbounded costs and applications to the control of queues
- 1 March 1976
- journal article
- research article
- Published by Cambridge University Press (CUP) in Advances in Applied Probability
- Vol. 8 (01) , 159-176
- https://doi.org/10.1017/s0001867800041379
Abstract
A discrete-time Markov decision model with a denumerable set of states and unbounded costs is considered. It is shown that the optimality equation of dynamic programming along with some additional, easily checked, conditions may be used to establish the optimality or ∊ -optimality of policies with respect to the average expected cost criterion. The results are used to derive optimal policies in two queueing examples.Keywords
This publication has 3 references indexed in Scilit:
- Optimal decision procedures for finite markov chains. Part I: ExamplesAdvances in Applied Probability, 1973
- A Solution to a Countable System of Equations Arising in Markovian Decision ProcessesThe Annals of Mathematical Statistics, 1967
- Denumerable State Markovian Decision Processes-Average Cost CriterionThe Annals of Mathematical Statistics, 1966