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
Engineering Solution of a Basic Call-Center Model
Management Science
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
Service Interruptions in Large-Scale Service Systems
Management Science
Control of systems with flexible multi-server pools: a shadow routing approach
Queueing Systems: Theory and Applications
A Fluid Approximation for Service Systems Responding to Unexpected Overloads
Operations Research
Shadow-Routing Based Control of Flexible Multiserver Pools in Overload
Operations Research
Overflow Networks: Approximations and Implications to Call Center Outsourcing
Operations Research
A Fluid Limit for an Overloaded X Model via a Stochastic Averaging Principle
Mathematics of Operations Research
Diffusion approximation for an overloaded X model via a stochastic averaging principle
Queueing Systems: Theory and Applications
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We consider how two networked large-scale service systems that normally operate separately, such as call centers, can help each other when one encounters an unexpected overload and is unable to immediately increase its own staffing. Our proposed control activates serving some customers from the other system when a ratio of the two queue lengths (numbers of waiting customers) exceeds a threshold. Two thresholds, one for each direction of sharing, automatically detect the overload condition and prevent undesired sharing under normal loads. After a threshold has been exceeded, the control aims to keep the ratio of the two queue lengths at a specified value. To gain insight, we introduce an idealized stochastic model with two customer classes and two associated service pools containing large numbers of agents. To set the important queue-ratio parameters, we consider an approximating deterministic fluid model. We determine queue-ratio parameters that minimize convex costs for this fluid model. We perform simulation experiments to show that the control is effective for the original stochastic model. Indeed, the simulations show that the proposed queue-ratio control with thresholds outperforms the optimal fixed partition of the servers given known fixed arrival rates during the overload, even though the proposed control does not use information about the arrival rates.