On the invariance principle for the first passage time
Mathematics of Operations Research
A heavy-traffic analysis of a closed queueing system with a GI/\infty service center
Queueing Systems: Theory and Applications
Designing a Call Center with Impatient Customers
Manufacturing & Service Operations Management
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
Heavy Traffic Limits for Queues with Many Deterministic Servers
Queueing Systems: Theory and Applications
Call Centers with Impatient Customers: Many-Server Asymptotics of the M/M/n + G Queue
Queueing Systems: Theory and Applications
Queues with Many Servers: The Virtual Waiting-Time Process in the QED Regime
Mathematics of Operations Research
Customer Abandonment in Many-Server Queues
Mathematics of Operations Research
Queueing Systems: Theory and Applications
Fluid models of many-server queues with abandonment
Queueing Systems: Theory and Applications
Diffusion approximations for open Jackson networks with reneging
Queueing Systems: Theory and Applications
Dynamic scheduling of a GI/GI/1+GI queue with multiple customer classes
Queueing Systems: Theory and Applications
Abandonment versus blocking in many-server queues: asymptotic optimality in the QED regime
Queueing Systems: Theory and Applications
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The asymptotic many-server queue with abandonments, G/GI/N + GI, is considered in the quality-and efficiency-driven (QED) regime. Here the number of servers and the offered load are related via the square-root rule, as the number of servers increases indefinitely. QED performance entails short waiting times and scarce abandonments (high quality) jointly with high servers' utilization (high efficiency), which is feasible when many servers cater to a single queue. For the G/GI/N + GI queue, we derive diffusion approximations for both its queue-length and virtual-waiting-time processes. Special cases, for which closed-form analysis is provided, are the G/M/N + GI and G/D/N + GI queues, thus expanding and generalizing existing results.