TY - JOUR
T1 - Robust heavy-traffic approximations for service systems facing overdispersed demand
AU - Mathijsen, Britt W.J.
AU - Janssen, A. J.E.M.
AU - van Leeuwaarden, Johan S.H.
AU - Zwart, Bert
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Arrival processes to service systems often display fluctuations that are larger than anticipated under the Poisson assumption, a phenomenon that is referred to as overdispersion. Motivated by this, we analyze a class of discrete-time stochastic models for which we derive heavy-traffic approximations that are scalable in the system size. Subsequently, we show how this leads to novel capacity sizing rules that acknowledge the presence of overdispersion. This, in turn, leads to robust approximations for performance characteristics of systems that are of moderate size and/or may not operate in heavy traffic.
AB - Arrival processes to service systems often display fluctuations that are larger than anticipated under the Poisson assumption, a phenomenon that is referred to as overdispersion. Motivated by this, we analyze a class of discrete-time stochastic models for which we derive heavy-traffic approximations that are scalable in the system size. Subsequently, we show how this leads to novel capacity sizing rules that acknowledge the presence of overdispersion. This, in turn, leads to robust approximations for performance characteristics of systems that are of moderate size and/or may not operate in heavy traffic.
KW - Heavy-traffic approximations
KW - Overdispersion
KW - Random walk
KW - Saddle point method
UR - http://www.scopus.com/inward/record.url?scp=85046720604&partnerID=8YFLogxK
U2 - 10.1007/s11134-018-9584-z
DO - 10.1007/s11134-018-9584-z
M3 - Article
C2 - 30956380
AN - SCOPUS:85046720604
SN - 0257-0130
VL - 90
SP - 257
EP - 289
JO - Queueing Systems
JF - Queueing Systems
IS - 3-4
ER -