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Flexible Staffing for Call Centers with Non-stationary Arrival Rates

In: Markov Decision Processes in Practice

Author

Listed:
  • Alex Roubos

    (CCmath)

  • Sandjai Bhulai

    (Vrije Universiteit Amsterdam)

  • Ger Koole

    (Vrije Universiteit Amsterdam)

Abstract

We consider a multi-period staffing problem of a single-skill call center. The call center is modeled as a multi-server queue in which the staffing levels can be changed only at specific moments in time. The objective is to set the staffing levels such that a service level constraint is met in the presence of time-varying arrival rates. We develop a Markov decision model to obtain time-dependent staffing levels for both the case where the arrival rate function is known as well as unknown. The characteristics of the optimal policies associated to the two cases are illustrated through a numerical study based on real-life data. We show that the optimal policies provide a good balance between staffing costs and the penalty probability for not meeting the service level.

Suggested Citation

  • Alex Roubos & Sandjai Bhulai & Ger Koole, 2017. "Flexible Staffing for Call Centers with Non-stationary Arrival Rates," International Series in Operations Research & Management Science, in: Richard J. Boucherie & Nico M. van Dijk (ed.), Markov Decision Processes in Practice, chapter 0, pages 487-503, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-47766-4_19
    DOI: 10.1007/978-3-319-47766-4_19
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    Cited by:

    1. Raik Stolletz, 2022. "Optimization of time-dependent queueing systems," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 481-483, April.
    2. Gabriel Zayas-Cabán & Mark E. Lewis, 2020. "Admission control in a two-class loss system with periodically varying parameters and abandonments," Queueing Systems: Theory and Applications, Springer, vol. 94(1), pages 175-210, February.

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