Basic concepts of optimization, Convex sets and covex functions
Simplex method, LP problem, slack variables
Derivative-free optimization methods
Fibonacci series and Golden Section, Brent method
Gradient based methods, Quasi-newton methods
Heuristic methods
Constrained optimization : Primal and dual methods
Multidisciplinary optimization problems
Programming aspects
Practical Work: exercises and labs on the design of optimisation algorithms on benchmark engineering problems.
The students will be able to: Understand different theoretical and computational aspects of a wide range of optimization
methods,
Use of optimization toolbox.
- Gestionnaire: Ina Taralova