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Further Results on Queues with Partial Correlation

Author

Listed:
  • Nasser Hadidi

    (University of Wisconsin-Stout, Menomonie, Wisconsin)

Abstract

As a sequel to the author's and Conolly and Choo's articles, this paper further investigates the effects of positive correlation between the underlying processes in queueing models. Having established that the waiting time distribution is hyperexponential for a certain service interarrival joint density, we examined the sensitivity of this distribution to the value of the correlation coefficient r (0 r r = 0 (conventional models) and r = 1 have long been known, we are able to illustrate the convergence of the waiting time density and respective moments to their limiting values.

Suggested Citation

  • Nasser Hadidi, 1985. "Further Results on Queues with Partial Correlation," Operations Research, INFORMS, vol. 33(1), pages 203-209, February.
    • Handle: RePEc:inm:oropre:v:33:y:1985:i:1:p:203-209
    DOI: 10.1287/opre.33.1.203
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    Cited by:

    1. Weimin Dai & Jian-Qiang Hu, 2022. "Correlated queues with service times depending on inter-arrival times," Queueing Systems: Theory and Applications, Springer, vol. 100(1), pages 41-60, February.
    2. Qixin Wang & Jian-Qiang Hu, 2024. "Queues with correlated inter-arrival and service times," Queueing Systems: Theory and Applications, Springer, vol. 108(1), pages 1-30, October.
    3. Civelek, Ismail & Biller, Bahar & Scheller-Wolf, Alan, 2021. "Impact of dependence on single-server queueing systems," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1031-1045.
    4. Nima Manafzadeh Dizbin & Barış Tan, 2019. "Modelling and analysis of the impact of correlated inter-event data on production control using Markovian arrival processes," Flexible Services and Manufacturing Journal, Springer, vol. 31(4), pages 1042-1076, December.
    5. O. J. Boxma & M. R. H. Mandjes, 2022. "Queueing and risk models with dependencies," Queueing Systems: Theory and Applications, Springer, vol. 102(1), pages 69-86, October.

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