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When Should a Roving Server Be Patient?

Author

Listed:
  • Mandyam M. Srinivasan

    (Management Science Program, College of Business Administration, The University of Tennessee, Knoxville, Tennessee 37996-0562)

  • Diwakar Gupta

    (Michael G. DeGroote School of Business, McMaster University, Hamilton, Ontario L8S 4M4, Canada)

Abstract

When polling systems are used to model real-world systems, it is typically assumed that the server switches continuously ("roves") even when there are no waiting jobs in the system. However, requiring the server to be patient, instead of having it rove, might be more realistic. Furthermore, operational control of these systems can be improved by knowing answers to questions like "under what circumstances should be roving server be patient?" and "at which stations?". This paper analyzes the patient server model and provides explicit expressions for the waiting time distributions, the mean waiting times and the pseudo-conservation law. Several variants of the patient server model are considered. We show that while the patient server mechanism is generally better than the roving server mechanism in the work-in-process (WIP) reduction sense, there do exist cases where roving is better. Counter-intuitive examples where reducing switchover time can increase WIP are also reported.

Suggested Citation

  • Mandyam M. Srinivasan & Diwakar Gupta, 1996. "When Should a Roving Server Be Patient?," Management Science, INFORMS, vol. 42(3), pages 437-451, March.
    • Handle: RePEc:inm:ormnsc:v:42:y:1996:i:3:p:437-451
    DOI: 10.1287/mnsc.42.3.437
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    Citations

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    Cited by:

    1. Legros, Benjamin & Jouini, Oualid & Akşin, O. Zeynep & Koole, Ger, 2020. "Front-office multitasking between service encounters and back-office tasks," European Journal of Operational Research, Elsevier, vol. 287(3), pages 946-963.
    2. Gupta, Diwakar & Gunalay, Yavuz & Srinivasan, Mandyam M., 2001. "The relationship between preventive maintenance and manufacturing system performance," European Journal of Operational Research, Elsevier, vol. 132(1), pages 146-162, July.
    3. Robert B. Cooper & Shun-Chen Niu & Mandyam M. Srinivasan, 1998. "When Does Forced Idle Time Improve Performance in Polling Models?," Management Science, INFORMS, vol. 44(8), pages 1079-1086, August.
    4. Gregory Dobson & Hsiao-Hui Lee & Arvind Sainathan & Vera Tilson, 2012. "A Queueing Model to Evaluate the Impact of Patient "Batching" on Throughput and Flow Time in a Medical Teaching Facility," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 584-599, October.

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