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Staffing a Call Center with Uncertain Arrival Rate and Absenteeism

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  • Ward Whitt

Abstract

This paper proposes simple methods for staffing a single‐class call center with uncertain arrival rate and uncertain staffing due to employee absenteeism. The arrival rate and the proportion of servers present are treated as random variables. The basic model is a multi‐server queue with customer abandonment, allowing non‐exponential service‐time and time‐to‐abandon distributions. The goal is to maximize the expected net return, given throughput benefit and server, customer‐abandonment and customer‐waiting costs, but attention is also given to the standard deviation of the return. The approach is to approximate the performance and the net return, conditional on the random model‐parameter vector, and then uncondition to get the desired results. Two recently‐developed approximations are used for the conditional performance measures: first, a deterministic fluid approximation and, second, a numerical algorithm based on a purely Markovian birth‐and‐death model, having state‐dependent death rates.

Suggested Citation

  • Ward Whitt, 2006. "Staffing a Call Center with Uncertain Arrival Rate and Absenteeism," Production and Operations Management, Production and Operations Management Society, vol. 15(1), pages 88-102, March.
  • Handle: RePEc:bla:popmgt:v:15:y:2006:i:1:p:88-102
    DOI: 10.1111/j.1937-5956.2006.tb00005.x
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    References listed on IDEAS

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    Cited by:

    1. Örmeci, E. Lerzan & Salman, F. Sibel & Yücel, Eda, 2014. "Staff rostering in call centers providing employee transportation," Omega, Elsevier, vol. 43(C), pages 41-53.
    2. Cohen, Asaf & Saha, Subhamay, 2021. "Asymptotic optimality of the generalized cμ rule under model uncertainty," Stochastic Processes and their Applications, Elsevier, vol. 136(C), pages 206-236.
    3. Andersen, Anders Reenberg & Nielsen, Bo Friis & Reinhardt, Line Blander & Stidsen, Thomas Riis, 2019. "Staff optimization for time-dependent acute patient flow," European Journal of Operational Research, Elsevier, vol. 272(1), pages 94-105.
    4. Mattia, Sara & Rossi, Fabrizio & Servilio, Mara & Smriglio, Stefano, 2017. "Staffing and scheduling flexible call centers by two-stage robust optimization," Omega, Elsevier, vol. 72(C), pages 25-37.
    5. Sanders, Nada R. & Graman, Gregory A., 2009. "Quantifying costs of forecast errors: A case study of the warehouse environment," Omega, Elsevier, vol. 37(1), pages 116-125, February.
    6. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.
    7. Robbins, Thomas R. & Harrison, Terry P., 2010. "A stochastic programming model for scheduling call centers with global Service Level Agreements," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1608-1619, December.
    8. Kayse Lee Maass & Boying Liu & Mark S. Daskin & Mary Duck & Zhehui Wang & Rama Mwenesi & Hannah Schapiro, 2017. "Incorporating nurse absenteeism into staffing with demand uncertainty," Health Care Management Science, Springer, vol. 20(1), pages 141-155, March.
    9. Sun, Bo & Sun, Xu & Tsang, Danny H.K. & Whitt, Ward, 2019. "Optimal battery purchasing and charging strategy at electric vehicle battery swap stations," European Journal of Operational Research, Elsevier, vol. 279(2), pages 524-539.

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