UE Numerical optimisation

User information

Please note that you are curently looking at the ongoing Academic Programs. Applications are now closed for this academic year (2020-2021) for licences, professional licences, masters, DUT and regulated health training. If you are interested for an application in 2021-2022, please click on this link for the appropriate Academic Programs.

Degrees incorporating this pedagocial element :


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


  • 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


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 or single session - Knowledge testing

Type of teaching providedMethodTypeDuration (min)Coefficient
Teaching Unit (UE)CC 100/100
Teaching Unit (UE)CT Written - supervised work120100/100

Session 2 - Knowledge testing

Type of teaching providedMethodTypeDuration (min)Coefficient
Teaching Unit (UE)CC Calculation report100/100
Teaching Unit (UE)CT Written or Oral120100/100