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On the Accuracy of Fluid Models for Capacity Sizing in Queueing Systems with Impatient Customers

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  • Achal Bassamboo

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208)

  • Ramandeep S. Randhawa

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

We consider queueing systems in which customers arrive according to a Poisson process and have exponentially distributed service requirements. The customers are impatient and may abandon the system while waiting for service after a generally distributed amount of time. The system incurs customer-related costs that consist of waiting and abandonment penalty costs. We study capacity sizing in such systems to minimize the sum of the long-term average customer-related costs and capacity costs. We use fluid models to derive prescriptions that are asymptotically optimal for large customer arrival rates. Although these prescriptions are easy to characterize, they depend intricately upon the distribution of the customers' time to abandon and may prescribe operating in a regime with offered load (the ratio of the arrival rate to the capacity) greater than 1. In such cases, we demonstrate that the fluid prescription is optimal up to O (1). That is, as the customer arrival rate increases, the optimality gap of the prescription remains bounded.

Suggested Citation

  • Achal Bassamboo & Ramandeep S. Randhawa, 2010. "On the Accuracy of Fluid Models for Capacity Sizing in Queueing Systems with Impatient Customers," Operations Research, INFORMS, vol. 58(5), pages 1398-1413, October.
  • Handle: RePEc:inm:oropre:v:58:y:2010:i:5:p:1398-1413
    DOI: 10.1287/opre.1100.0815
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    References listed on IDEAS

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    9. Sunil Kumar & Ramandeep S. Randhawa, 2010. "Exploiting Market Size in Service Systems," Manufacturing & Service Operations Management, INFORMS, vol. 12(3), pages 511-526, September.
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    Cited by:

    1. Ramandeep S. Randhawa, 2016. "Optimality gap of asymptotically derived prescriptions in queueing systems," Queueing Systems: Theory and Applications, Springer, vol. 83(1), pages 131-155, June.
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    3. Kawai, Yosuke & Takagi, Hideaki, 2015. "Fluid approximation analysis of a call center model with time-varying arrivals and after-call work," Operations Research Perspectives, Elsevier, vol. 2(C), pages 81-96.
    4. J. G. Dai & Shuangchi He, 2010. "Customer Abandonment in Many-Server Queues," Mathematics of Operations Research, INFORMS, vol. 35(2), pages 347-362, May.
    5. Tolga Tezcan & Jiheng Zhang, 2014. "Routing and Staffing in Customer Service Chat Systems with Impatient Customers," Operations Research, INFORMS, vol. 62(4), pages 943-956, August.
    6. Alexey Piunovskiy & Yi Zhang, 2011. "Accuracy of fluid approximations to controlled birth-and-death processes: absorbing case," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 73(2), pages 159-187, April.
    7. Dongyuan Zhan & Amy R. Ward, 2019. "Staffing, Routing, and Payment to Trade off Speed and Quality in Large Service Systems," Operations Research, INFORMS, vol. 67(6), pages 1738-1751, November.
    8. Ping Cao & Jingui Xie, 2016. "Optimal control of a multiclass queueing system when customers can change types," Queueing Systems: Theory and Applications, Springer, vol. 82(3), pages 285-313, April.
    9. Zhenghua Long & Nahum Shimkin & Hailun Zhang & Jiheng Zhang, 2020. "Dynamic Scheduling of Multiclass Many-Server Queues with Abandonment: The Generalized cμ / h Rule," Operations Research, INFORMS, vol. 68(4), pages 1128-1230, July.
    10. Noa Zychlinski, 2023. "Applications of fluid models in service operations management," Queueing Systems: Theory and Applications, Springer, vol. 103(1), pages 161-185, February.
    11. Achal Bassamboo & Ramandeep Singh Randhawa, 2016. "Scheduling Homogeneous Impatient Customers," Management Science, INFORMS, vol. 62(7), pages 2129-2147, July.
    12. Jeunghyun Kim & Ramandeep S. Randhawa & Amy R. Ward, 2018. "Dynamic Scheduling in a Many-Server, Multiclass System: The Role of Customer Impatience in Large Systems," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 285-301, May.
    13. Chenguang (Allen) Wu & Achal Bassamboo & Ohad Perry, 2019. "Service System with Dependent Service and Patience Times," Management Science, INFORMS, vol. 65(3), pages 1151-1172, March.
    14. Junfei Huang & Avishai Mandelbaum & Hanqin Zhang & Jiheng Zhang, 2017. "Refined Models for Efficiency-Driven Queues with Applications to Delay Announcements and Staffing," Operations Research, INFORMS, vol. 65(5), pages 1380-1397, October.
    15. Alexander L. Stolyar & Tolga Tezcan, 2011. "Shadow-Routing Based Control of Flexible Multiserver Pools in Overload," Operations Research, INFORMS, vol. 59(6), pages 1427-1444, December.
    16. Eugene Furman & Adam Diamant & Murat Kristal, 2021. "Customer Acquisition and Retention: A Fluid Approach for Staffing," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4236-4257, November.
    17. Delgado-Alvarez, Carlos A. & van Ackere, Ann & Larsen, Erik R & Arango-Aramburo, Santiago, 2017. "Managing capacity at a service facility: An experimental approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 216-228.
    18. Shuangchi He, 2020. "Diffusion Approximation for Efficiency-Driven Queues When Customers Are Patient," Operations Research, INFORMS, vol. 68(4), pages 1265-1284, July.
    19. Vahid Sarhangian & Hossein Abouee-Mehrizi & Opher Baron & Oded Berman, 2018. "Threshold-Based Allocation Policies for Inventory Management of Red Blood Cells," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 347-362, May.
    20. Zhenghua Long & Jiheng Zhang, 2019. "Virtual allocation policies for many-server queues with abandonment," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 90(3), pages 399-451, December.
    21. Bo Zhang & Johan S. H. van Leeuwaarden & Bert Zwart, 2012. "Staffing Call Centers with Impatient Customers: Refinements to Many-Server Asymptotics," Operations Research, INFORMS, vol. 60(2), pages 461-474, April.
    22. Achal Bassamboo & Ramandeep S. Randhawa & Assaf Zeevi, 2010. "Capacity Sizing Under Parameter Uncertainty: Safety Staffing Principles Revisited," Management Science, INFORMS, vol. 56(10), pages 1668-1686, October.
    23. Itai Gurvich & Junfei Huang & Avishai Mandelbaum, 2014. "Excursion-Based Universal Approximations for the Erlang-A Queue in Steady-State," Mathematics of Operations Research, INFORMS, vol. 39(2), pages 325-373, May.
    24. A. Korhan Aras & Xinyun Chen & Yunan Liu, 2018. "Many-server Gaussian limits for overloaded non-Markovian queues with customer abandonment," Queueing Systems: Theory and Applications, Springer, vol. 89(1), pages 81-125, June.

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