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Comparison of Policies for Routing Customers to Parallel Queueing Systems

Author

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  • D. J. Houck

    (AT&T Bell Laboratories, Holmdel, New Jersey)

Abstract

This paper studies a queueing system with two groups of servers, each with a separate queue, and with arriving customers routed irrevocably to one of the two queues. One natural policy for routing arriving customers is to send them to the queue with the shortest expected delay. Although this shortest delay routing policy (SDR) is known to be optimal if each server group has one server and the service time distribution has nondecreasing failure rate, little is known about the general multiserver case, even with exponential service times. In this paper we show, using a theoretical upper bound, that an optimal policy would produce delays that are almost identical to what would result from combining the two groups. In addition, our simulation results show that SDR performs nearly optimally in every case considered.

Suggested Citation

  • D. J. Houck, 1987. "Comparison of Policies for Routing Customers to Parallel Queueing Systems," Operations Research, INFORMS, vol. 35(2), pages 306-310, April.
    • Handle: RePEc:inm:oropre:v:35:y:1987:i:2:p:306-310
    DOI: 10.1287/opre.35.2.306
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    Citations

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    Cited by:

    1. Jacko, Peter, 2008. "Marginal productivity index policies for problems of admission control and routing to parallel queues with delay," DES - Working Papers. Statistics and Econometrics. WS ws087225, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. P S Ansell & K D Glazebrook & C Kirkbride, 2003. "Generalised ‘join the shortest queue’ policies for the dynamic routing of jobs to multi-class queues," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 379-389, April.
    3. Brooks, James D. & Kar, Koushik & Mendonça, David J., 2016. "Allocation of flows in closed bipartite queueing networks," European Journal of Operational Research, Elsevier, vol. 255(2), pages 333-344.
    4. Benjaafar, Saifallah, 1995. "Performance bounds for the effectiveness of pooling in multi-processing systems," European Journal of Operational Research, Elsevier, vol. 87(2), pages 375-388, December.
    5. Ivo J. B. F. Adan & Onno J. Boxma & Stella Kapodistria & Vidyadhar G. Kulkarni, 2016. "The shorter queue polling model," Annals of Operations Research, Springer, vol. 241(1), pages 167-200, June.
    6. V.D. Dinopoulou & C. Melolidakis, 2001. "Asymptotically optimal component assembly plans in repairable systems and server allocation in parallel multiserver queues," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(8), pages 732-746, December.
    7. Melissa A. Valentine & Amy C. Edmondson, 2015. "Team Scaffolds: How Mesolevel Structures Enable Role-Based Coordination in Temporary Groups," Organization Science, INFORMS, vol. 26(2), pages 405-422, April.
    8. Ick-Hyun Nam, 2001. "Dynamic Scheduling for a Flexible Processing Network," Operations Research, INFORMS, vol. 49(2), pages 305-315, April.

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