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Risk measures and their application to staffing nonstationary service systems

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  • Pender, Jamol

Abstract

In this paper, we explore the use of static risk measures from the mathematical finance literature to assess the performance of some standard nonstationary queueing systems. To do this we study two important queueing models, namely the infinite server queue and the multi-server queue with abandonment. We derive exact expressions for the value of many standard risk measures for the Mt/M/∞, Mt/G/∞, and Mt/Mt/∞ queueing models. We also derive Gaussian based approximations for the value of risk measures for the Erlang-A queueing model. Unlike more traditional approaches of performance analysis, risk measures offer the ability to satisfy the unique and specific risk preferences or tolerances of service operations managers. We also show how risk measures can be used for staffing nonstationary systems with different risk preferences and assess the impact of these staffing policies via simulation.

Suggested Citation

  • Pender, Jamol, 2016. "Risk measures and their application to staffing nonstationary service systems," European Journal of Operational Research, Elsevier, vol. 254(1), pages 113-126.
    • Handle: RePEc:eee:ejores:v:254:y:2016:i:1:p:113-126
    DOI: 10.1016/j.ejor.2016.03.012
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    Citations

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    Cited by:

    1. Jerome Niyirora & Jamol Pender, 2016. "Optimal staffing in nonstationary service centers with constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(8), pages 615-630, December.
    2. Li, Dongmin & Hu, Qingpei & Wang, Lujia & Yu, Dan, 2019. "Statistical inference for Mt/G/Infinity queueing systems under incomplete observations," European Journal of Operational Research, Elsevier, vol. 279(3), pages 882-901.
    3. Vincent Tsz Fai Chow & Zheng Cui & Daniel Zhuoyu Long, 2022. "Target-Oriented Distributionally Robust Optimization and Its Applications to Surgery Allocation," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2058-2072, July.
    4. Eugene Furman & Alex Cressman & Saeha Shin & Alexey Kuznetsov & Fahad Razak & Amol Verma & Adam Diamant, 2021. "Prediction of personal protective equipment use in hospitals during COVID-19," Health Care Management Science, Springer, vol. 24(2), pages 439-453, June.
    5. William A. Massey & Jamol Pender, 2018. "Dynamic rate Erlang-A queues," Queueing Systems: Theory and Applications, Springer, vol. 89(1), pages 127-164, June.

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