Many-server loss models with non-poisson time-varying arrivals

Many-server loss models with non-poisson time-varying arrivals

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Article ID: iaor20172409
Volume: 64
Issue: 3
Start Page Number: 177
End Page Number: 202
Publication Date: Apr 2017
Journal: Naval Research Logistics (NRL)
Authors: ,
Keywords: queues: applications, simulation
Abstract:

This article proposes an approximation for the blocking probability in a many‐server loss model with a non‐Poisson time‐varying arrival process and flexible staffing (number of servers) and shows that it can be used to set staffing levels to stabilize the time‐varying blocking probability at a target level. Because the blocking probabilities necessarily change dramatically after each staffing change, we randomize the time of each staffing change about the planned time. We apply simulation to show that (i) the blocking probabilities cannot be stabilized without some form of randomization, (ii) the new staffing algorithm with randomiation can stabilize blocking probabilities at target levels and (iii) the required staffing can be quite different when the Poisson assumption is dropped.

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