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Rare-Event Simulation of Non-Markovian Queueing Networks Using a State-Dependent Change of Measure Determined Using Cross-Entropy

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  • Pieter-Tjerk de Boer

Abstract

A method is described for the efficient estimation of small overflow probabilities in nonMarkovian queueing network models. The method uses importance sampling with a state-dependent change of measure, which is determined adaptively using the cross-entropy method, thus avoiding the need for a detailed mathematical analysis. Experiments show that the use of rescheduling is needed in order to get a significant simulation speedup, and that the method can be used to estimate overflow probabilities in a two-node tandem queue network model for which simulation using a state-independent change of measure does not work well. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Pieter-Tjerk de Boer, 2005. "Rare-Event Simulation of Non-Markovian Queueing Networks Using a State-Dependent Change of Measure Determined Using Cross-Entropy," Annals of Operations Research, Springer, vol. 134(1), pages 69-100, February.
    • Handle: RePEc:spr:annopr:v:134:y:2005:i:1:p:69-100:10.1007/s10479-005-5725-y
    DOI: 10.1007/s10479-005-5725-y
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    References listed on IDEAS

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    1. Rubinstein, Reuven Y., 1997. "Optimization of computer simulation models with rare events," European Journal of Operational Research, Elsevier, vol. 99(1), pages 89-112, May.
    2. P. T. de Boer & D. P. Kroese & R. Y. Rubinstein, 2004. "A Fast Cross-Entropy Method for Estimating Buffer Overflows in Queueing Networks," Management Science, INFORMS, vol. 50(7), pages 883-895, July.
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    Cited by:

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    2. David F. Muñoz & Héctor Gardida & Hugo Velázquez & Jorge D. Ayala, 2022. "Simulation models to support the preliminary electoral results program for the Mexican Electoral Institute," Annals of Operations Research, Springer, vol. 316(2), pages 1141-1156, September.

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