Service-Level Differentiation in Many-Server Service Systems via Queue-Ratio Routing

Published Online:https://doi.org/10.1287/opre.1090.0736

References

  • Armony M. Dynamic routing in large-scale service systems with heterogenous servers. Queueing Systems (2005) 51(3–4):287–329CrossrefGoogle Scholar
  • Armony M., Mandelbaum A. Routing and staffing in large-scale service systems: The case of homogeneous impatient customers and heterogeneous servers. (2008) . Working paper, New York University, New York, and Technion—Israel Institute of Technology, Haifa, IsraelGoogle Scholar
  • Atar R. Scheduling control for queueing systems with many servers: Asymptotic optimality in heavy traffic. Ann. Appl. Probab. (2005) 15(4):2606–2650CrossrefGoogle Scholar
  • Bassamboo A., Zeevi A. Staffing telephone call centers subject to service-level constraints: An approximate approach via constraint dualization. (2008) . Working paper, Northwestern University, Evanston, IL, and Columbia University, New YorkGoogle Scholar
  • Bassamboo A., Harrison J. M., Zeevi A. Dynamic routing and admission control in high volume service systems: Asymptotic analysis via multi-scale fluid limits. Queueing Systems (2006a) 51(3–4):249–285CrossrefGoogle Scholar
  • Bassamboo A., Harrison J. M., Zeevi A. Design and control of a large call center: Asymptotic analysis of an LP-based method. Oper. Res. (2006b) 54(3):419–435LinkGoogle Scholar
  • Borst S., Mandelbaum A., Reiman M. Dimensioning large call centers. Oper. Res. (2004) 52(1):17–34LinkGoogle Scholar
  • Feldman Z., Gurvich I., Whitt W. Managing quality of service in call centers via queue-ratio routing: Asymptotic analysis and simulation-based optimization. (2007) . Working paper, Columbia University, New YorkGoogle Scholar
  • Gans N., Koole G., Mandelbaum A. Telephone call centers: Tutorial, review and research prospects. Manufacturing Service Oper. Management (2003) 5(2):79–141LinkGoogle Scholar
  • Gurvich I., Whitt W. Queue-and-idleness-ratio controls in many-server service systems. Math. Oper. Res. (2009a) 34(2):363–396LinkGoogle Scholar
  • Gurvich I., Whitt W. Scheduling flexible servers with convex delay costs in many-server service systems. Manufacturing Service Oper. Management (2009b) 11(2):237–253LinkGoogle Scholar
  • Gurvich I., Armony M., Mandelbaum A. Service-level differentiation in call centers with fully flexible servers. Management Sci. (2008) 54(2):279–294LinkGoogle Scholar
  • Gurvich I., Luedtke J., Tezcan T. Staffing call centers with uncertain demand forecasts: A chance constrained optimization approach. (2008) . Working paper, Northwestern University, Evanston, ILGoogle Scholar
  • Halfin S., Whitt W. Heavy-traffic limits for queues with many exponential servers. Oper. Res. (1981) 29(3):567–587LinkGoogle Scholar
  • Mandelbaum A., Stolyar A. Scheduling flexible servers with convex delay costs: Heavy-traffic optimality of the generalized cμ-rule. Oper. Res. (2004) 52(6):836–855LinkGoogle Scholar
  • Van Mieghem J. A. Dynamic scheduling with convex delay costs: The generalized cμ rule. Ann. Appl. Probab. (1995) 5(3):809–833CrossrefGoogle Scholar
  • Van Mieghem J. A. Due date scheduling: Asymptotic optimality of generalized longest queue and generalized largest delay rules. Oper. Res. (2003) 51(1):113–122LinkGoogle Scholar
  • Wallace R. B., Whitt W. A staffing algorithm for call centers with skill-based routing. Manufacturing Service Oper. Management (2005) 7(4):276–294LinkGoogle Scholar
  • Whitt W. A multi-class fluid model for a contact center with skill-based routing. Internat. J. Electronics Comm. (AEU) (2006) 60(2):95–102CrossrefGoogle Scholar
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