Optimization models and methods [ LINMA2471 ]
5.0 crédits ECTS
30.0 h + 22.5 h
1q
| Teacher(s) |
Glineur François ;
|
| Language |
French
|
Place
of the course |
Louvain-la-Neuve
|
| Main themes |
1. Basic concepts and classification of optimization problems.
2. Introduction to three categories of problems : linear optimization, convex optimization and nonlinear optimization ; for each of them :
a.What problems can we formulate ?
(presentation of the class of problems that can be modelled)
b.How can we solve them ?
(description and analysis of relevant solving techniques)
3.Modelling and practical resolution of real-world problems using a modelling language and/or specialized software.
|
| Aims |
Learn how to formulate, analyze and solve optimization problems.
|
| Content |
Course
1. Optimization models
Linear optimization and duality.
Convex optimization, duality and conic formulation.
Nonlinear optimization and optimality conditions.
2. Optimization methods
Interior-point methods for linear optimization, conic optimization (quadratic and semidefinite) and convex optimization ; algorithmic complexity.
Trust-region methods and Nelder-Mead method for nonlinear optimization.
Exercises and projects
Formulation and resolution of concrete problems.
AMPL modelling language.
|
| Other information |
Prerequisites :
Basic notions of real calculus, linear algebra and basic notions in optimization (material from the course INMA 2702)
Evaluation :
Group projects during the semester and final written exam ; course material available on the icampus web site.
|
Cycle et année
d'étude |
> Master [120] in Statistics: General
> Master [120] in Computer Science
> Master [120] in Computer Science and Engineering
> Master [120] in Mathematical Engineering
> Master [120] in Physical Engineering
> Master [120] in Biomedical Engineering
|
Faculty or entity
in charge |
> MAP
|
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