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Staffing of time-varying queues using a geometric discrete time modelling approach

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  • Xi Chen

    (Lancaster University)

  • Dave Worthington

    (Lancaster University)

Abstract

Many queueing systems with time-dependent arrivals require time-dependent staffing to provide satisfactory service levels at reasonable cost. Feldman et al. (Manag Sci 54(2):324–338, 2008) proposed an iterative staffing algorithm designed to deliver time-stable performance in which successive iterations were evaluated via simulation experiments. In this paper we present and evaluate an analytical queueing model combined with an iterative staffing algorithm to be used for setting staffing levels to achieve time-stable performance in call centre type queues. Empirical results show that the method to be considerably faster than simulation based methods and considerably more accurate than the industry standard analytical methods.

Suggested Citation

  • Xi Chen & Dave Worthington, 2017. "Staffing of time-varying queues using a geometric discrete time modelling approach," Annals of Operations Research, Springer, vol. 252(1), pages 63-84, May.
    • Handle: RePEc:spr:annopr:v:252:y:2017:i:1:d:10.1007_s10479-015-2058-3
    DOI: 10.1007/s10479-015-2058-3
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    References listed on IDEAS

    as
    1. Wall, A.D. & Worthington, D.J., 2007. "Time-dependent analysis of virtual waiting time behaviour in discrete time queues," European Journal of Operational Research, Elsevier, vol. 178(2), pages 482-499, April.
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    5. Izady, Navid & Worthington, Dave, 2012. "Setting staffing requirements for time dependent queueing networks: The case of accident and emergency departments," European Journal of Operational Research, Elsevier, vol. 219(3), pages 531-540.
    6. Ward Whitt, 2005. "Engineering Solution of a Basic Call-Center Model," Management Science, INFORMS, vol. 51(2), pages 221-235, February.
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    12. Zohar Feldman & Avishai Mandelbaum & William A. Massey & Ward Whitt, 2008. "Staffing of Time-Varying Queues to Achieve Time-Stable Performance," Management Science, INFORMS, vol. 54(2), pages 324-338, February.
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    Cited by:

    1. Notz, Pascal M. & Wolf, Peter K. & Pibernik, Richard, 2023. "Prescriptive analytics for a multi-shift staffing problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 887-901.

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