Jose Blanchet (2013) Optimal Sampling of Overflow Paths in Jackson Networks. Mathematics of Operations Research 38(4):698-719. https://doi.org/10.1287/moor.2013.0586

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Abstract

We consider the problems of computing overflow probabilities at level N in any subset of stations in a Jackson network and of simulating sample paths conditional on overflow. We construct algorithms that take O(N) function evaluations to estimate such overflow probabilities within a prescribed relative accuracy and to simulate paths conditional on overflow at level N. The algorithms that we present are optimal in the sense that the best possible performance that can be expected for conditional sampling involves Ω(N) running time. As we explain in our development, our techniques have the potential to be applicable to more general classes of networks.

Authors
Jose Blanchet
Publication date
2013/11
Journal
Mathematics of Operations Research
Volume
38
Issue
4
Pages
698-719
Publisher
INFORMS