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Queueing Models (queueing + models)

Distribution by Scientific Domains
Mathematics and Statistics75%

Selected Abstracts

Subexponential Distributions , Large Deviations with Applications to Insurance and Queueing Models

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 1 2004
Aleksandras Baltr
Summary This paper presents a fine large-deviations theory for heavy-tailed distributions whose tails are heavier than exp(,,t and have finite second moment. Asymptotics for first passage times are derived. The results are applied to estimate the finite time ruin probabilities in insurance as well as the busy period in a GI/G/1 queueing model. [source]

What you should know about queueing models to set staffing requirements in service systems

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 5 2007
Ward Whitt
Abstract One traditional application of queueing models is to help set staffing requirements in service systems, but the way to do so is not entirely straightforward, largely because demand in service systems typically varies greatly by the time of day. This article discusses ways,old and new,to cope with that time-varying demand. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007 [source]

Coping with Time-Varying Demand When Setting Staffing Requirements for a Service System

PRODUCTION AND OPERATIONS MANAGEMENT, Issue 1 2007
Linda V. Green
We review queueing-theory methods for setting staffing requirements in service systems where customer demand varies in a predictable pattern over the day. Analyzing these systems is not straightforward, because standard queueing theory focuses on the long-run steady-state behavior of stationary models. We show how to adapt stationary queueing models for use in nonstationary environments so that time-dependent performance is captured and staffing requirements can be set. Relatively little modification of straightforward stationary analysis applies in systems where service times are short and the targeted quality of service is high. When service times are moderate and the targeted quality of service is still high, time-lag refinements can improve traditional stationary independent period-by-period and peak-hour approximations. Time-varying infinite-server models help develop refinements, because closed-form expressions exist for their time-dependent behavior. More difficult cases with very long service times and other complicated features, such as end-of-day effects, can often be treated by a modified-offered-load approximation, which is based on an associated infinite-server model. Numerical algorithms and deterministic fluid models are useful when the system is overloaded for an extensive period of time. Our discussion focuses on telephone call centers, but applications to police patrol, banking, and hospital emergency rooms are also mentioned. [source]