Abstract
The first part of this chapter presented the definition of a continuous-time Markov chain with two properties, and the introduction of a B&D process with some special examples such as homogeneous Poisson process as a pure birth process, and the population model as a B&D process. The second part of the chapter was an extension of a B&D process to the B&D queueing models including the general B&D queueing model, M/M/1 queueing model, and M/M/m queueing model. Finally, the last part of the chapter introduced Kolmogorov’s backward/forward equations, the infinitesimal generator matrix of a CTMC, and the time-reversibility condition for a CTMC. Several examples and problems including those related to the population model, the server systems, and the patient states have been provided and solved.
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Bas, E. (2019). Continuous-Time Markov Chains. In: Basics of Probability and Stochastic Processes. Springer, Cham. https://doi.org/10.1007/978-3-030-32323-3_14
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DOI: https://doi.org/10.1007/978-3-030-32323-3_14
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32322-6
Online ISBN: 978-3-030-32323-3
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