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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 Biomedical Engineering
> Master [120] in Computer Science
> Master [120] in Computer Science and Engineering
> Master [120] in Mathematical Engineering
> Master [120] in Statistics: General
Faculty or entity
in charge
> MAP


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