Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9663736 | European Journal of Operational Research | 2005 | 16 Pages |
Abstract
This paper presents an improved version of a componentwise bounding algorithm for the state probability vector of nearly completely decomposable Markov chains, and on an application it provides the first numerical results with the type of algorithm discussed. The given two-level algorithm uses aggregation and stochastic comparison with the strong stochastic (st) order. In order to improve accuracy, it employs reordering of states and a better componentwise probability bounding algorithm given st upper- and lower-bounding probability vectors. Results in sparse storage show that there are cases in which the given algorithm proves to be useful.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Nihal Pekergin, TuÄrul Dayar, Denizhan N. Alparslan,