UCL - Discrete stochastic models

[INMA2470]

[30h + 22.5h] 5 credits

This course is taught in the 1st semester.

Teacher(s): Philippe Chevalier

Language: French

Level: Second

Aims
Main themes
Content and teaching methods
Other information (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)

Aims

Introduction to stochastic processes used for modeling random systems and their most common applications. In particular we study methods to compute the operating characteristics of such processes.

Main themes

Introduction to stochastic models in operations research. Study of renewal processes, Markov chains, Markov Processes, Markov Decision Processes. Applications to inventory models, queuing models, branching processes, random walks, etc.

Content and teaching methods

- Introduction to stochastic processes with a discrete state-space
- Discrete time Markov chains with finite and infinite state-space
- Continuous time Markov processes (and semi-Markov processes)
- Renewal processes and stopping rules
- Poisson processes, birth and death processes
- Queuing theory and queuing networks
- Various applications such as inventory models, maintenance models, reliability, job-shops,

Other information (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)

no special information