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Simulation models of real-life systems often assume stationary (homogeneous) Poisson arrivals. Therefore, when nonstationary arrival processes are required it is natural to assume Poisson arrivals with a time-varying arrival rate. For many systems, however, this provides an inaccurate representation of the arrival process which is either more or less(More)
This paper introduces a method to model and simulate non-stationary, non-renewal arrival processes that depends only on the analyst setting intuitive and easily controllable parameters. Thus, it is suitable for assessing the impact of non-stationary, non-exponential, and non-independent arrivals on simulated performance when they are suspected. A specific(More)
Providing probabilistic analysis of queueing models can be difficult when the input distributions are non-Markovian. In response, a plethora of methods have been developed to approximate a general renewal process by a process with the time between renewals being distributed as a phase type random variable, which allows the resulting queueing models to(More)
This paper introduces a method to model and simulate nonstationary, non-renewal arrival processes that depends only on the analyst setting intuitive and easily con-trollable parameters. Thus, it is suitable for assessing the impact of nonstationary, non-exponential and non-independent arrivals on simulated performance when they are suspected but no data are(More)
In this paper we examine a tandem network of queueing nodes where a nonstation-ary external Markovian arrival process feeds the initial upstream node. We develop methods for modeling the departure flow from any upstream node in its role as the arrival process to the immediate downstream node, and employ various techniques to match the interarrival moments(More)
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