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Nicola, V.F. and Zaburnenko, T.S.
(2006)
Efficient Importance Sampling Heuristics for the Simulation of Population Overflow in Feed-Forward Queueing Networks.
In: Proceedings of the Sixth Rare-Event Simulation Workshop, RESIM2006, 8 - 10 October 2006, Bamberg, Germany.
pp. 144-152.
Otto-Friedrich University.
ISBN not assigned
Full text available as:
 AbstractIn this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in feed-forward networks. This heuristic attempts to approximate the “optimal��? state-dependent change of measure without the need for difficult analysis or costly optimization involved in other recently proposed adaptive importance sampling algorithms. Preliminary simulation experiments with a 4-node feed-forward network yield asymptotically efficient estimates, with relative error increasing at most linearly in the overflow level, where state-independent importance sampling is demonstrably ineffective.
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