A Simple Numerical Approach for Infinite-State Markov Chains
- 27 July 1991
- journal article
- research article
- Published by Cambridge University Press (CUP) in Probability in the Engineering and Informational Sciences
- Vol. 5 (3) , 285-295
- https://doi.org/10.1017/s0269964800002096
Abstract
This paper presents a simple and practical approach to solving the equilibrium equations for a class of Markov chains with an infinite number of states. Markov chains arising in queueing and inventory applications often have the property that the state probabilities exhibit a geometric tail behavior. The basic idea of the approach is to reduce the infinite system of linear equations to a finite system using the geometric tail behavior of the equilibrium probabilities. The reduction typically leads to a remarkably small system of linear equations that can be routinely solved by a Gaussian elimination method. An application is given to the single-server queue with scheduled arrivals.Keywords
This publication has 4 references indexed in Scilit:
- Convergent Iterations for Computing Stationary Distributions of Markov ChainsSIAM Journal on Algebraic Discrete Methods, 1986
- Regenerative Analysis and Steady State Distributions for Markov ChainsOperations Research, 1985
- A Class of Approximations for the Waiting Time Distribution in aGI/G/1 Queueing SystemBell System Technical Journal, 1982
- A NUMERICAL METHOD FOR THE STEADY-STATE PROBABILITIES OF A G1/G/C QUEUING SYSTEM IN A GENERAL CLASSJournal of the Operations Research Society of Japan, 1976