Learning outcomes

This course presents an introduction to the theoretical and numerical methods most commonly used in heuristic optimization method theory. The course is built around several articles where these methods are presented and articles where applications are presented.

Goals

The goal is to understand the theory and use it to replicate the results of an article or book chapter

Content

The course changes every year depending on the students, their interests and the topics of their master thesis. 

Assessment method

The exam consists of two parts. A written report of 10-20 pages that the student gives to the professor and the assistant in charge of TD (at the latest) one week before the date of the oral examination. And an oral, about twenty minutes, during which the student presents his results and the methods used.
 
Depending on the number of students, group work may be considered. In this case, all members of the group will present the oral together and specific questions per student will be asked.

Sources, references and any support material

The list changes according to the subjects chosen by the students

Language of instruction

Français
Training Study programme Block Credits Mandatory
Standard 0 6
Standard 0 6
Standard 0 6
Standard 0 6
Standard 0 6
Standard 1 6
Standard 1 6
Standard 1 6
Standard 1 6
Standard 1 6