Degrees incorporating this pedagocial element :
Description
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
Recommended prerequisite
linear algebra, differential calculus
Targeted skills
Recognise and classify optimisation problems
Solve optimisation problems using adequate algorithms and methods
Practical implementation
Knowledge assessment methods
Session 1 ou session unique - Contrôle des connaissances
| Type of teaching provided | Method | Type | Duration (min) | Coefficient |
|---|---|---|---|---|
| Teaching Unit (UE) | 100/100 | |||
| Teaching Unit (UE) | Written - supervised work | 120 | 100/100 |
Session 2 - Contrôle des connaissances
| Type of teaching provided | Method | Type | Duration (min) | Coefficient |
|---|---|---|---|---|
| Teaching Unit (UE) | Calculation report | 100/100 | ||
| Teaching Unit (UE) | Written or Oral | 120 | 100/100 |
Courses offered by :
In brief
Period : Semester 8Credits : 6
Number of hours
- Lectures (CM) & Teaching Unit (UE) : 33h
- Practical work (TP) : 16.5h
Location(s) : Grenoble
Language(s) : English
Contact(s)
Program director
International students
Open to exchange students