Strong approximations for a Kumar-Seidman network under a priority service discipline

2010 ◽  
Vol 26 (4) ◽  
pp. 587-596
Author(s):  
Lin Wu ◽  
Chuan-xi Zhu ◽  
Yun-jiang Wu
Keyword(s):  
Service Discipline ◽  
Strong Approximations ◽  
Priority Service ◽  
Priority Service Discipline ◽  
A Priority

STABILITY OF THE MULTI-TYPE REENTRANT LINES WITH TYPE PRIORITY SERVICE DISCIPLINE

2009 ◽  
Vol 26 (03) ◽  
pp. 341-349
Author(s):  
JIANKUI YANG
Keyword(s):  
Lyapunov Function ◽  
Fluid Model ◽  
Queueing Network ◽  
Special Kind ◽  
Service Discipline ◽  
Priority Service ◽  
Priority Service Discipline ◽  
Reentrant Lines ◽  
The Stability

This paper studies the fluid model of a special kind of multi-type queueing network with type priority. The fluid of the same type in the same station is operated under last buffer first served (LBFS) policy. The stability of this kind of fluid model is proved via the Lyapunov function.

scholarly journals A General Framework to Compare Announcement Accuracy: Static vs. LES-Based Announcement

2020 ◽  
Author(s):  
Achal Bassamboo ◽  
Rouba Ibrahim
Keyword(s):  
Operations Management ◽  
Call Center ◽  
Service Providers ◽  
Waiting Times ◽  
Real Life ◽  
Weighted Average ◽  
Superior Performance ◽  
Service Discipline ◽  
Priority Service ◽  
Real Time Information

Service providers often share delay information, in the form of delay announcements, with their customers. In practice, simple delay announcements, such as average waiting times or a weighted average of previously delayed customers, are often used. Our goal in this paper is to gain insight into when such announcements perform well. Specifically, we compare the accuracies of two announcements: (i) a static announcement that does not exploit real-time information about the state of the system and (ii) a dynamic announcement, specifically the last-to-enter-service (LES) announcement, which equals the delay of the last customer to have entered service at the time of the announcement. We propose a novel correlation-based approach that is theoretically appealing because it allows for a comparison of the accuracies of announcements across different queueing models, including multiclass models with a priority service discipline. It is also practically useful because estimating correlations is much easier than fitting an entire queueing model. Using a combination of queueing-theoretic analysis, real-life data analysis, and simulation, we analyze the performance of static and dynamic announcements and derive an appropriate weighted average of the two which we demonstrate has a superior performance using both simulation and data from a call center. This paper was accepted by Vishal Gaur, operations management.

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