The lagged PSA for estimating peak congestion in multiserver Markovian queues with periodic arrival rates

The lagged PSA for estimating peak congestion in multiserver Markovian queues with periodic arrival rates

0.00 Avg rating0 Votes
Article ID: iaor1998979
Country: United States
Volume: 43
Issue: 1
Start Page Number: 80
End Page Number: 87
Publication Date: Jan 1997
Journal: Management Science
Authors: ,
Keywords: statistics: inference
Abstract:

We propose using a modification of the simple peak hour approximation (SPHA) for estimating peak congestion in multiserver queueing systems with exponential service times and time-varying periodic Poisson arrivals. This lagged pointwise stationary approximation (lagged PSA) is obtained by first estimating the time of the actual peak congestion by the time of peak congestion in an infinite server model and then substituting the arrival rate at this time in the corresponding stationary finite server model. We show that the lagged PSA is always more accurate than the SPHA and results in dramatically smaller errors when average service times are greater than a half an hour (based on a 24 hour period). More importantly, the lagged PSA reliably identifies proper staffing levels to meet targeted performance levels to keep congestion low.

Reviews

Required fields are marked *. Your email address will not be published.