Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
Optimal Routing In Output-Queued Flexible Server Systems
Probability in the Engineering and Informational Sciences
Maximizing Queueing Network Utility Subject to Stability: Greedy Primal-Dual Algorithm
Queueing Systems: Theory and Applications
Queueing Systems: Theory and Applications
Fluid Models for Multiserver Queues with Abandonments
Operations Research
Optimal control of parallel server systems with many servers in heavy traffic
Queueing Systems: Theory and Applications
Scheduling Flexible Servers with Convex Delay Costs in Many-Server Service Systems
Manufacturing & Service Operations Management
On a Data-Driven Method for Staffing Large Call Centers
Operations Research
Responding to Unexpected Overloads in Large-Scale Service Systems
Management Science
Control of systems with flexible multi-server pools: a shadow routing approach
Queueing Systems: Theory and Applications
The cμ/θ Rule for Many-Server Queues with Abandonment
Operations Research
On the asymptotic optimality of the cμ/θ rule under ergodic cost
Queueing Systems: Theory and Applications
A Fluid Approximation for Service Systems Responding to Unexpected Overloads
Operations Research
Robust Design and Control of Call Centers with Flexible Interactive Voice Response Systems
Manufacturing & Service Operations Management
A large-scale service system with packing constraints: minimizing the number of occupied servers
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
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We consider a general parallel server system model with multiple customer classes and several flexible multiserver pools, in the many-server asymptotic regime where the input rates and server pool sizes are scaled up linearly to infinity. Service of a customer brings a constant reward, which depends on its class. The objective is to maximize the long-run reward rate. Our primary focus is on overloaded systems. Unlike in the case when the system is not overloaded, where the main decision is how to allocate resources to incoming customers, in this case it is also crucial to determine which customers will be admitted to the system. We propose a real-time, parsimonious, robust routing policy, SHADOW-RM, which does not require the knowledge of customer input rates and does not solve any optimization problem explicitly, and we prove its asymptotic optimality. Then, by combining SHADOW-RM with another policy, SHADOW-LB, proposed in our previous work for systems that are not overloaded, we suggest policy SHADOW-TANDEM, which automatically and seamlessly detects overload and reduces to one of the schemes, SHADOW-RM or SHADOW-LB, accordingly. Extensive simulations demonstrate a remarkably good performance of proposed policies.