Course on Numerical Optimization
Tuesdays and Wednesdays, 10:35 - 12:35,
Celestijnenlaan 200 S.00.05
Starting on September 23, 2008
Course announcementAim of the course (H03E3a ,6 credit points, 17 lectures, 7 exercise
sessions) is to provide the
basics of numerical optimization methods and to enable the participants to
apply and adapt
these methods to practical engineering problems. From October 24 on, the
course will be
accompanied by weekly computer exercise sessions. A final written exam in
January 2009 will
conclude the course.
Contents of the Course
Part I: Introduction
1. Fundamental Concepts of Optimization
2. Types of Optimization Problems
3. Convex Optimization, Linear Programming (LP)
Part II: Unconstrained Optimization
4. Estimation and Fitting Problems
5. Newton Type Optimization Methods
6. Gauss-Newton and Levenberg-Marquard
7. Calculating Derivatives
8. Trust Region vs. Line Search Methods
Part III: Constrained Optimization
9. Karush-Kuhn-Tucker Optimality Conditions
10. Parametric Sensitivity of Solutions
11. Quadratic Programming (QP): Active Set
12. Interior Point Methods
13. Sequential Quadratic Programming
14. Globalisation Strategies
15. Optimization Modelling, Slack Variables
16. Optimal Control Problems
17. Summary of the Lecture
Lecture: Moritz Diehl, Professor for Optimization in Engineering,
ESAT 02.82,
moritz.diehl@esat.kuleuven.be
Exercises: Boris Houska, Hans Joachim Ferreau
The course is partly based on the book Numerical Optimization by J.
Nocedal and S. Wright, Springer Verlag, and on the free book:
Convex Optimization by S. Boyd and L. Vandenberghe, Cambridge
