Course ObjectiveWithin this course you will get acquainted with stochastic processes and
models for waiting lines (queueing models). The learning objectives are:
- To know the assumptions and formulations of some fundamental
stochastic processes and queueing models.
- To be able to analyze the fundamental models mentioned above and apply
similar analysis techniques to related models.
- To formulate a model based on a practical situation and recognize
which model is applicable.
- To be able interpret the final result of stochastic models and
understand the practical implications (like economies of scale, impact
of variability and critical load).
Course ContentStochastic processes and queueing models are often applied to model
practical situations where uncertainty is involved. This course mainly
focuses on Markov chains and queueing models. A key element is the
theoretical development of such models with the emphasis on modeling and
its analysis. In addition, the models are motivated by applications.
More specifically, the fundamental stochastic processes and queueing
models that we study are: Markov chains in discrete and continuous time,
the Poisson process, the M/M/1 queue, the Erlang delay and loss model,
birth-death processes, the M/G/1 queue and the waiting-time paradox.
Teaching MethodsLectures and tutorials.
Method of AssessmentTwo mid-term exams and a hand-in assignment in period 1 (presented in
the 4th week that should be turned in 2 weeks later). The resit involves
LiteratureKulkarni, V.G., Introduction to Modeling and Analysis of Stochastic
Systems, Springer Texts in Statistics (also available as e-book via
Adan, I.J.B.F., and Resing, J.A.C., Queueing Theory, online lecture
notes (made available via Canvas)
Recommended background knowledgeProbability theory
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||dr. W. Kager|
|Examiner||dr. W. Kager|
dr. W. Kager
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Seminar, Lecture|
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