Efficient Simulation of Population Overflow in Parallel Queues

V.F. Nicola, T.S. Zaburnenko

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    In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overflow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.
    Original languageUndefined
    Title of host publicationProceedings of the 2006 Winter Simulation Conference, WSC'06
    Number of pages8
    ISBN (Print)1424405017
    Publication statusPublished - Dec 2006
    Event2006 Winter Simulation Conference - Monterey, United States
    Duration: 3 Dec 20066 Dec 2006

    Publication series



    Conference2006 Winter Simulation Conference
    Abbreviated titleWSC 2006
    CountryUnited States
    Other3 - 6 December 2006


    • EWI-9066
    • METIS-237909
    • IR-66871

    Cite this

    Nicola, V. F., & Zaburnenko, T. S. (2006). Efficient Simulation of Population Overflow in Parallel Queues. In Proceedings of the 2006 Winter Simulation Conference, WSC'06 (pp. 398-405). WSC.