Stochastic Offered Load Processes in Service Systems

Seminar
Thursday, March 07, 2013
6:00 PM
ENS 637
Free and open to the public

Many challenges arise in the operations management of service systems with uncertain time-varying arrivals, non-exponential service and patience times, and complex network structures. Stochastic offered load processes have been shown to provide useful insights in capacity planning and performance analysis of large-scale service systems. In this talk, we focus on stochastic offered load processes in non-Markovian many-server queueing systems with dependence among interarrival times and among service times. Dependence among interarrival times commonly occurs when some of the arrivals are overflows from another system; the arrival process is more bursty as a consequence. Dependent service times can occur in many systems. For example, in a hospital emergency room, there may be multiple patients associated with the same medical incident, so that their required treatment can be highly correlated. The goal is to study the impact of these forms of dependence upon system performance and capacity planning. We derive the approximate stationary and transient distributions of stochastic offered load processes by proving a functional central limit theorem under the assumptions that the sequence of interarrival times satisfies a functional central limit theorem and the sequence of service times satisfies certain mixing conditions. We show how the stationary and transient distributions can be used to give effective approximations of delay probabilities and provide insights on staffing (a refined square root staffing rule) for such systems.

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Speaker

Guodong Pang

Assistant Professor
Penn State University

Dr. Guodong Pang is currently an assistant professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at Pennsylvania State University and holds the Marcus Career Professorship. Dr. Pang received his Ph.D. in Operations Research at Columbia University in 2010. His research interests are in applied probability, stochastic networks, queueing systems, with applications in service systems (customer contact centers, healthcare), energy (smart grids), data centers, cloud computing and telecommunications. His work has been published in journals such as: Management Science, Manufacturing & Service Operations Management, Annals of Applied Probability, Advances in Applied Probability and Queueing Systems.