 | Study programme 2019-2020 | Français | |
| Non-Linear Optimization | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-MARO-036 |
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| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 22 | 10 | 0 | 0 | 0 | Q1 |
| Organisational online arrangements for the end of Q3 2019-2020 assessments (Covid-19) |
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| Description of the modifications to the Q3 2019-2020 online assessment procedures (Covid-19) |
| The examination focuses on understanding the ex-cathedra course at the level of theory, exercises and the implementation of optimization algorithms. In a given time, the exam will consist of answering theory questions, solving exercises and implementing algorithms. If one of the grades of one of the three parts (theory, exercises, implementation) is less than 7 (over 20), then the final grade will be equal to the minimum grade of the three grades. For theory and exercises, the written documents must be photographed and deposited on Moodle (respecting the time allowed). The files corresponding to the implementation of algorithms must also be uploaded to Moodle (respecting the time allowed). The schedule must be absolutely respected. |
Content of Learning Activity
The objective of this course is to provide students with the basic tools to address and solve nonlinear optimization problems.
The course will be divided into two main parts: modelization and methods
The first part aims to teach students to determine the type of optimization problems (linear, quadratic, convex, etc.) and to characterize optimal solutions in the more general context of problems with equality and inequality constraints.
In the second part, the most widespread numerical methods will be introduced.
Attendance at theory/exercises classes of at least 80% is required. Attendance at practical sessions and seminars is mandatory.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Face to face
Type of Teaching Activity/Activities
- Cours magistraux
- Conférences
- Exercices dirigés
- Utilisation de logiciels
- Démonstrations
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)