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Time Dependent Priority Queues

Author

Listed:
  • Leonard Kleinrock

    (University of California, Los Angeles, California)

  • Roy P. Finkelstein

    (Stanford Research Institute, Menlo Park, California)

Abstract

Considered is a class of r th order delay-dependent priority queuing disciplines in which a customer from the p th priority group, who arrives at time T , has a priority q p ( t ) at time t given by q p ( t ) = b p ( t − T ) r . The main result states that the expected wait on queue for p -type customers in an r th order system with parameter set [ b p ] is identical to the wait in any other such system, say one of order r ′ with parameter set [ b p ′] if these parameters are chosen in the proper manner. From this, using the results due to Kleinrock for the first order systems, we obtain the expected wait on queue, conditioned on the priority groups, for any r th order system. This class of queuing disciplines ranges from Cobham's fixed priority system (for r → 0) to the first-come-first-served system (for r → ∞). For the case of two priority groups the set { b p } is chosen so as to minimize a class of delay-dependent cost functions. Results from a computer simulation are given to display the behavior of the waiting time variance.

Suggested Citation

  • Leonard Kleinrock & Roy P. Finkelstein, 1967. "Time Dependent Priority Queues," Operations Research, INFORMS, vol. 15(1), pages 104-116, February.
  • Handle: RePEc:inm:oropre:v:15:y:1967:i:1:p:104-116
    DOI: 10.1287/opre.15.1.104
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    Cited by:

    1. Li, Na & Stanford, David A., 2016. "Multi-server accumulating priority queues with heterogeneous servers," European Journal of Operational Research, Elsevier, vol. 252(3), pages 866-878.
    2. Noah Gans & Ger Koole & Avishai Mandelbaum, 2003. "Telephone Call Centers: Tutorial, Review, and Research Prospects," Manufacturing & Service Operations Management, INFORMS, vol. 5(2), pages 79-141, September.
    3. Jiang, Yangzi & Abouee-Mehrizi, Hossein & Diao, Yuhe, 2020. "Data-driven analytics to support scheduling of multi-priority multi-class patients with wait time targets," European Journal of Operational Research, Elsevier, vol. 281(3), pages 597-611.
    4. Öner-Közen, Miray & Minner, Stefan, 2017. "Impact of priority sequencing decisions on on-time probability and expected tardiness of orders in make-to-order production systems with external due-dates," European Journal of Operational Research, Elsevier, vol. 263(2), pages 524-539.
    5. Mingang Yin & Ming Yan & Yu Guo & Minghe Liu, 2023. "Analysis of a Pre-Emptive Two-Priority Queuing System with Impatient Customers and Heterogeneous Servers," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
    6. Na Li & David A. Stanford & Peter Taylor & Ilze Ziedins, 2017. "Nonlinear Accumulating Priority Queues with Equivalent Linear Proxies," Operations Research, INFORMS, vol. 65(6), pages 1712-1721, December.
    7. Val Andrei Fajardo & Steve Drekic, 2017. "Waiting Time Distributions in the Preemptive Accumulating Priority Queue," Methodology and Computing in Applied Probability, Springer, vol. 19(1), pages 255-284, March.
    8. Moshe Haviv & Liron Ravner, 2016. "Strategic bidding in an accumulating priority queue: equilibrium analysis," Annals of Operations Research, Springer, vol. 244(2), pages 505-523, September.

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