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Optimizing Call Center Staffing Using Simulation and Analytic Center Cutting-Plane Methods

  • Júlíus Atlason

    ()

    (THOR Development and Research, Reykjavík, Iceland)

  • Marina A. Epelman

    ()

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109)

  • Shane G. Henderson

    ()

    (School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853)

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    We consider the problem of minimizing staffing costs in an inbound call center, while maintaining an acceptable level of service in multiple time periods. The problem is complicated by the fact that staffing level in one time period can affect the service levels in subsequent periods. Moreover, staff schedules typically take the form of shifts covering several periods. Interactions between staffing levels in different time periods, as well as the impact of shift requirements on the staffing levels and cost, should be considered in the planning. Traditional staffing methods based on stationary queueing formulas do not take this into account. We present a simulation-based analytic center cutting-plane method to solve a sample average approximation of the problem. We establish convergence of the method when the service-level functions are discrete pseudoconcave. An extensive numerical study of a moderately large call center shows that the method is robust and, in most of the test cases, outperforms traditional staffing heuristics that are based on analytical queueing methods.

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    File URL: http://dx.doi.org/10.1287/mnsc.1070.0774
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    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 54 (2008)
    Issue (Month): 2 (February)
    Pages: 295-309

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    Handle: RePEc:inm:ormnsc:v:54:y:2008:i:2:p:295-309
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    1. Ingolfsson, Armann & Amanul Haque, Md. & Umnikov, Alex, 2002. "Accounting for time-varying queueing effects in workforce scheduling," European Journal of Operational Research, Elsevier, vol. 139(3), pages 585-597, June.
    2. Ward Whitt, 1991. "The Pointwise Stationary Approximation for Mt/Mt/s Queues Is Asymptotically Correct As the Rates Increase," Management Science, INFORMS, vol. 37(3), pages 307-314, March.
    3. Otis B. Jennings & Avishai Mandelbaum & William A. Massey & Ward Whitt, 1996. "Server Staffing to Meet Time-Varying Demand," Management Science, INFORMS, vol. 42(10), pages 1383-1394, October.
    4. J. L. Goffin & A. Haurie & J. P. Vial, 1992. "Decomposition and Nondifferentiable Optimization with the Projective Algorithm," Management Science, INFORMS, vol. 38(2), pages 284-302, February.
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