Optimal pricing in queueing systems with quality of service constraints
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Imagine a queueing system with cost sensitive customers. In this situation the service provider is presented with a simple mechanism for regulating usage. The natural goals of such regularization are to maximize revenue and, for systems with finite capacity, to ensure a given quality of service measure. Quality of service may be defined in various ways, but typical examples include minimizing delays in service or the probability of users being blocked. Therefore, dynamic pricing schemes arise as an alternative to building to capacity. We investigate these issues in the context of the general Erlang blocking system or carried traffic model. More specifically, given such a system where arrival rates are user cost dependent, we attempt to maximize revenue while keeping the probability of blocking below some fixed level. An approximate algorithm based on an exact analysis an infinite server or offered traffic model is presented.