A Multi-Level Solution Algorithm for Steady-State Markov Chains

@inproceedings{Horton1994AMS,
  title={A Multi-Level Solution Algorithm for Steady-State Markov Chains},
  author={Graham Horton and Scott T. Leutenegger},
  booktitle={SIGMETRICS},
  year={1994}
}
A new iterative algorithm, the multi-level algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial differential equations. Initial results of numerical experiments are reported, showing significant reductions in computation time, often an order of magnitude… CONTINUE READING
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MUPPALA: SPNP: stochastic Petri net package

G. CIARDO, J. K. TRWEDI
Proc. of the Third Int. Workshop on Petri Nets and Performance Models (PNPM89), • 1989
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