Stabilizing Customer Abandonment in Many-Server Queues with Time-Varying Arrivals
Yunan Liu () and
Ward Whitt ()
Additional contact information
Yunan Liu: Department of Industrial Engineering, North Carolina State University, Raleigh, North Carolina 27695
Ward Whitt: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027
Operations Research, 2012, vol. 60, issue 6, 1551-1564
Abstract:
An algorithm is developed to determine time-dependent staffing levels to stabilize the time-dependent abandonment probabilities and expected delays at positive target values in the M t / GI / s t + GI many-server queueing model, which has a nonhomogeneous Poisson arrival process (the M t ), has general service times (the first GI ), and allows customer abandonment according to a general patience distribution (the + GI ). New offered-load and modified-offered-load approximations involving infinite-server models are developed for that purpose. Simulations show that the approximations are effective. A many-server heavy-traffic limit in the efficiency-driven regime shows that (i) the proposed approximations achieve the goal asymptotically as the scale increases, and (ii) it is not possible to simultaneously stabilize the mean queue length in the same asymptotic regime.
Keywords: staffing; capacity planning; many-server queues; queues with time-varying arrivals; queues with abandonment; infinite-server queues; offered-load approximations; service systems (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)
Downloads: (external link)
http://dx.doi.org/10.1287/opre.1120.1104 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:60:y:2012:i:6:p:1551-1564
Access Statistics for this article
More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().