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Single Server Queueing-Location Models with Rejection

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  • Rajan Batta

    (State University of New York at Buffalo, Buffalo, New York 14260)

Abstract

This paper considers the problem of locating a single server on a network while explicitly accounting for queueing of calls for service. Calls from a node can either all be accepted or all be rejected by the service system. Two models are considered. In the first model a call can be rejected independent of the state of the system when the call arrives. In the second model, an arriving call can be rejected only if it finds the server busy. The queueing systems are analyzed for both models. A greedy heuristic is developed which, parametrically in the arrival rate of calls, determines the location of the server and the rejection strategies at nodes. Extreme case analysis with respect to the arrival rate is investigated. A numerical example illustrates our results. Our major observation is that the rejection strategies for calls are dependent on the arrival rate, and the choice of model.

Suggested Citation

  • Rajan Batta, 1988. "Single Server Queueing-Location Models with Rejection," Transportation Science, INFORMS, vol. 22(3), pages 209-216, August.
    • Handle: RePEc:inm:ortrsc:v:22:y:1988:i:3:p:209-216
    DOI: 10.1287/trsc.22.3.209
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    Cited by:

    1. Elena Fernández & Yolanda Hinojosa & Justo Puerto, 2005. "Filtering Policies in Loss Queuing Network Location Problems," Annals of Operations Research, Springer, vol. 136(1), pages 259-283, April.
    2. E. Carrizosa & E. Conde & M. Muñoz-Márquez, 1998. "Admission Policies in Loss Queueing Models with Heterogeneous Arrivals," Management Science, INFORMS, vol. 44(3), pages 311-320, March.
    3. Vladimir Marianov & Daniel Serra, 1996. "Probabilistic maximal covering location-allocation models with constrained waiting time or queue length for congested systems," Economics Working Papers 177, Department of Economics and Business, Universitat Pompeu Fabra.
    4. V Marianov & T B Boffey & R D Galvão, 2009. "Optimal location of multi-server congestible facilities operating as M/E r /m/N queues," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(5), pages 674-684, May.
    5. Gregory Dobson & Euthemia Stavrulaki, 2007. "Simultaneous price, location, and capacity decisions on a line of time‐sensitive customers," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(1), pages 1-10, February.
    6. Chen, Heng & Hu, Zhangchen & Solak, Senay, 2021. "Improved delivery policies for future drone-based delivery systems," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1181-1201.

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