Journal
AUTOMATICA
Volume 45, Issue 7, Pages 1639-1648Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2009.03.007
Keywords
Perturbation analysis; Customer-average performance; Policy iteration
Funding
- National Natural Science Foundation of China [60574064]
- Hong Kong RGC
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We consider the optimization of queueing systems with service rates depending on system states. The optimization criterion is the long-run customer-average performance, which is an important performance metric, different from the traditional time-average performance. We first establish, with perturbation analysis, a difference equation of the customer-average performance in closed networks with exponentially distributed service times and state-dependent service rates. Then we propose a policy iteration optimization algorithm based on this difference equation. This algorithm can be implemented on-line with a single sample path and does not require knowing the routing probabilities of queueing systems. Finally, we give numerical experiments which demonstrate the efficiency of our algorithm. This paper gives a new direction to efficiently optimize the customer-centric performance in queueing systems. (C) 2009 Elsevier Ltd. All rights reserved.
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