An adaptive aggregation/disaggregation algorithm for hierarchical Markovian models
type: Item
instance of: scholarly article
title: An adaptive aggregation/disaggregation algorithm for hierarchical Markovian models
zbMATH Open document ID: 1001.60088
DOI: 10.1016/S0377-2217(98)00088-5
author: Peter Buchholz
published in: European Journal of Operational Research
publication date: 2002-08-18T00:00:00Z
review text: The analysis of continuous time Markov chains with huge state spaces requires considerable numerical effort. The author develops an algorithm for the evaluation of the stationary probabilities vector applicable to a quite general class of models. Hierarchically structured chains can be described by a generator matrix with a compact tensor representation. The algorithm combines SOR iterations exploiting the tensor structure with adaptive aggregation/disaggregation steps. Several examples are given to compare the performance of different variants of the algorithm.
reviewed by: Helmut Wegmann
Mathematics Subject Classification ID: 60K10
Mathematics Subject Classification ID: 90B22
Mathematics Subject Classification ID: 60K25
zbMATH DE Number: 1783251
zbMATH Keywords: Markov processes
zbMATH Keywords: hierarchical models
zbMATH Keywords: steady state analysis
zbMATH Keywords: iterative techniques
zbMATH Keywords: aggregation/disaggregation
MaRDI profile type: Publication
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full work available at URL: s0377-2217(98)00088-5
OpenAlex ID: W1969730878
description: scientific article; zbMATH DE number 1783251