Semi-Markov Queueing Models is a class of stochastic queueing models in which the system transitions between states according to a semi-Markov process, distinguished from standard Markovian models by allowing arbitrary, non-exponential distributions for service and inter-arrival times through the incorporation of embedded Markov chains and holding time distributions.
158
Publications
6.6K
Citations
236
Authors
145
Institutions
Publications per year
2017–2026
7
Publications
158
1–5 of 158
Authors
236
- MF
11
h-index
- EÇ
5
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- JH
4
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- TT
4
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- RL
3
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1–5 of 236
Institutions
145
University of Michigan
Ann Arbor, United States
5 h-index
6 publications
250 citations
Columbia University
New York, United States
5 h-index
6 publications
201 citations
Purdue University West Lafayette
West Lafayette, United States
5 h-index
5 publications
313 citations
Northwestern University
Evanston, United States
5 h-index
5 publications
212 citations
Florida Institute of Technology
Melbourne, United States
4 h-index
6 publications
103 citations
Eindhoven University of Technology
Eindhoven, The Netherlands
4 h-index
5 publications
134 citations
Pennsylvania State University
State College, United States
4 h-index
4 publications
585 citations
AT&T (United States)
Bedminster, United States
4 h-index
9 publications
371 citations
1–8 of 145
Venues
- Advances in Applied Probability
AAP · 18 publications · 778 citations
16
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- Journal of Applied Probability
JAP · 22 publications · 671 citations
14
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- Operations Research
11 publications · 625 citations
11
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- Stochastic Models
6 publications · 96 citations
6
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- Communications in Statistics Stochastic Models
6 publications · 421 citations
6
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1–5