Modelling and Optimization

Objectives

At the end of this module, the student will have understood and be able to explain :

- Various approaches to analyze and evaluate the performances of discrete event system DES

- Various types of modelling adapted to the problems considered (deterministic of stochastic models, numerical and combinatorics optimization models, models of concurrency)

-Algorithms available to solve these problems.

The student will be able to :

- Model and solve operational research problems (optimization, linear programming, graphs, stochastic process) and discrete event systems problems

- Model stochastic systems, such as a network of queues, using Markov chains. Comptute their stationary performance measures, and dimension its capacity

- Model a DES by Petri net, analyse the properties of the Petri net by various methods of analysis (exhaustive and structural).

Form of assessment

The evaluation of outcome prior learning is made as a continuous training during the semester. According ot the teaching, the assessment will be different: as a written exam, an oral exam, a record, a written report, peers review...