Call Centers with Impatient Customers: Many-Server Asymptotics of the M/M/n + G Queue
Queueing Systems: Theory and Applications
Evaluating arrival rate uncertainty in call centers
Proceedings of the 38th conference on Winter simulation
Fluid Models for Multiserver Queues with Abandonments
Operations Research
Approximations for the M/GI/N+GI type call center
Queueing Systems: Theory and Applications
Balking and reneging in m/g/s systems exact analysis and approximations
Probability in the Engineering and Informational Sciences
Proceedings of the 40th Conference on Winter Simulation
Manufacturing & Service Operations Management
The Impact of Delay Announcements in Many-Server Queues with Abandonment
Operations Research
Responding to Unexpected Overloads in Large-Scale Service Systems
Management Science
Two fluid approximations for multi-server queues with abandonments
Operations Research Letters
Contact center: information systems design
Journal of Intelligent Manufacturing
First in Line Waiting Times as a Tool for Analysing Queueing Systems
Operations Research
Delay predictors for customer service systems with time-varying parameters
Proceedings of the Winter Simulation Conference
Workforce Management in Periodic Delivery Operations
Transportation Science
| Hi-index | 0.01 |
An algorithm is developed to rapidly compute approximations for all the standard steady-state performance measures in the basic call-center queueing modelM/GI/s/r+GI, which has a Poisson arrival process, independent and identically distributed (IID) service times with a general distribution,s servers,r extra waiting spaces and IID customer abandonment times with a general distribution. Empirical studies of call centers indicate that the service-time and abandon-time distributions often are not nearly exponential, so that it is important to go beyond the MarkovianM/M/s/r+M special case, but the general service-time and abandon-time distributions make the realistic model very difficult to analyze directly. The proposed algorithm is based on an approximation by an appropriate MarkovianM/M/s/r+M(n) queueing model, whereM(n) denotes state-dependent abandonment rates. After making an additional approximation, steady-state waiting-time distributions are characterized via their Laplace transforms. Then the approximate distributions are computed by numerically inverting the transforms. Simulation experiments show that the approximation is quite accurate. The overall algorithm can be applied to determine desired staffing levels, e.g., the minimum number of servers needed to guarantee that, first, the abandonment rate is below any specified target value and, second, that the conditional probability that an arriving customer will be served within a specified deadline, given that the customer eventually will be served, is at least a specified target value.