Catalogue des formations

Diplômes intégrant cet élément pédagogique :

• Master Mathématiques et applications

Descriptif

This program combines case studies coming from real life problems or models and lectures providing the mathematical and numerical backgrounds.

Contents:

• Introduction, classification, examples.
• Theoretical results: convexity and compacity, optimality conditions, KT theorem
• Algorithmic for unconstrained optimisation (descent, line search, (quasi) Newton)
• Algorithms for non differentiable problems
• Algorithms for constrained optimisation: penalisatio, SQP methods
• Applications

Pré-requis recommandés

Basic algebra (linear spaces, matrix computation) Basic calculus (Norm, Banach spaces, Hilbert spaces, basic differential calculus) The students should be able to compute the gradient and the Hessian of real functions on IR^n and also differentials of simple functions such as quadratic forms.

Compétences visées

Recognise and classify optimisation problems

Solve optimisation problems using adequate algorithms and methods

Practical implementation

Modalités de contrôle des connaissances

Session 1 ou session unique - Contrôle des connaissances

Nature	Type	Nature d'évaluation	Durée (min)	Coeff.
UE				100/100
UE		Ecrit - devoir surveillé	120	100/100

Session 2 - Contrôle des connaissances

Nature	Type	Nature d'évaluation	Durée (min)	Coeff.
UE		Report de notes		100/100
UE		Ecrit ou Oral	120	100/100

Informations complémentaires

Lieu(x) : Grenoble
Langue(s) : Anglais