- Department of Applied Mathematics
Discrete event process, definition, random distribution, and probability. Basic processes, process of revitalisation. Markov process, Markov models, Kendall classification, model M/M/1, models M/M/n. Non-markovian models, model M/C/n, models G/G/n. Models with continuous flow. Serve process, examples Petri net.
- Syllabus of lectures:
1.Introduction, queuing model, examples.
2.Discrete event models, definition, form of notation, random distribution, and probability.
3.Basic processes - homogenous, ordinary processes, Poisson process, process of revitalisation.
4.Markov processes, set of Kolmogorov differential equations.
5.Markov model, Kendall classification.
6.Model M/M/1, number of customers, distribution of arrival rate and waiting time in queue, queuing systems.
7.Models M/M/a, stability condition, characteristics of a system, system M/M/Ą, system with a finite time of queuing.
8.Nonmarkovian models, model M/G/a, system with generally distributed service.
10.Model with continuous flow.
11.Serve process, introduction. Equilibrium in queuing model.
12.Serve process, examples. Model of an open server.
- Syllabus of tutorials:
- Study Objective:
- Study materials:
Bacceli F., Brémaud P.: Elements of Queuing Theory, Springer - Verlag, Applications of Mathematics 26, 1994
Kleinrock L.: Queuing Systems. orig. John Wiley &Sons, ruský překlad Moskva, 1979
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: