Adaptive Importance Sampling Simulation of Queueing Networks

Pieter-Tjerk de Boer, V.F. Nicola, N. Rubinstein, Reuven Y. Rubinstein

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    Abstract

    In this paper, a method is presented for the efficient estimation of rare-event (overflow) probabilities in Jackson queueing networks using importance sampling. The method differs in two ways from methods discussed in most earlier literature: the change of measure is state-dependent, i.e., it is a function of the content of the buffers, and the change of measure is determined using a cross-entropy-based adaptive procedure. This method yields asymptotically efficient estimation of overflow probabilities of queueing models for which it has been shown that methods using a stateindependent change of measure are not asymptotically efficient. Numerical results demonstrating the effectiveness of the method are presented as well.
    Original languageUndefined
    Title of host publicationThe 2000 Winter Simulation Conference (WSC'00)
    Place of PublicationOrlando, Florida, USA
    PublisherIEEE
    Pages646-655
    Number of pages10
    ISBN (Print)0-7803-6582-8
    DOIs
    Publication statusPublished - Dec 2000

    Publication series

    Name
    PublisherIEEE
    Volume1

    Keywords

    • EWI-7723
    • METIS-119564
    • IR-19042

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