A successive censoring algorithm for a system of connected LDQBD-processes

Niek Baer, Ahmad Al Hanbali (), Richard J. Boucherie () and Jan-Kees van Ommeren ()
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Niek Baer: University of Twente
Ahmad Al Hanbali: King Fahd University of Petroleum and Minerals
Richard J. Boucherie: University of Twente
Jan-Kees van Ommeren: University of Twente

Annals of Operations Research, 2022, vol. 310, issue 2, No 4, 389-410

Abstract: Abstract We consider a Markov Chain in which the state space is partitioned into sets where both transitions within sets and between sets have a special structure. Transitions within each set constitute a finite level dependent quasi-birth-and-death-process (LDQBD), and transitions between sets are restricted to six types of transitions. These latter types are needed to preserve the sets structure in the reduction step of our algorithm. Specifically, we present a successive censoring algorithm, based on matrix analytic methods, to obtain the stationary distribution of this system of connected LDQBD-processes.

Keywords: Successive censoring algorithm; Matrix analytic methods; Connected level dependent QBD-processes; Steady state analysis; Exact aggregation/disaggregation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-020-03903-2

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