Approximation algorithm and perfect sampler for closed jackson networks with single servers

S. Kijima, T. Matsui

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In this paper, we propose the first fully polynomial-time randomized approximation scheme (FPRAS) for closed Jackson networks with single servers. Our algorithm is based on the Markov chain Monte Carlo (MCMC) method, and our scheme returns an approximate solution, for which the size of error satisfies a given error rate. We propose two Markov chains: one is for approximate sampling, and the other is for perfect sampling based on the monotone coupling from the past algorithm.

Original languageEnglish
Pages (from-to)1484-1503
Number of pages20
JournalSIAM Journal on Computing
Volume38
Issue number4
DOIs
Publication statusPublished - Nov 7 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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