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Perturbation theory for unbounded Markov reward processes with applications to queueing. (English) Zbl 0642.60099
Consider a discrete time, discrete state Markov chain where a reward r(i) is obtained every time when the chain enters state i. The function r(.) needs not be bounded; only a weak quasi-bounding condition is assumed. The problem: If the transition probabilities and/or the reward function are perturbated to a certain amount, what will be the effect on the average reward and the finite horizon reward. The results are applied to an M/M/1 queue and on overflow model.
Reviewer: H.Daduna

60K30 Applications of queueing theory (congestion, allocation, storage, traffic, etc.)
90C47 Minimax problems in mathematical programming
90B22 Queues and service in operations research
90C31 Sensitivity, stability, parametric optimization
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