Official Course Description
- LTH Course Description (SV)
- NF Course Description (SV)
- LTH Course Description (EN)
- NF Course Description (EN)
The aim of the course is to present basic optimization theory, and to give an overview of the most important methods and their practical use.
Contents: Quadratic forms and matrix factorisation. Convexity. The theory of optimization with and without constraints: Lagrange functions, Kuhn-Tucker theory. Duality. Methods for optimization without constraints: line search, steepest descent, Newton methods, conjugate directions, non-linear least squares optimization. Methods for optimization with constraints: linear optimization, quadratic programming, penalty and barrier methods.
This course previously had the code FMA051
- Autumn, second half 2019 : Biomedical Engineering, Computer Science and Engineering, Electrical Engineering, Engineering Physics, Industrial Engineering and Management, Engineering Mathematics