Contents |
Course Code
IAM 665 (9700665)
Credit
(3-0) 3
Prerequisites
Consent of instructors
Content/Aims
Learning Outcomes
Suggested Textbooks/Resources
There is no textbook for the course. The material will be based on some of the references below and recent research papers:
- A. Ben-Tal, A. Nemirovski, Lectures on Modern Convex Optimization : Analysis, Algorithms, and Engineering Applications, SIAM, 2001.
- S. Boyd, L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004.
- P. Deuflhard, Newton Methods for Nonlinear Problems, Springer, 2004.
- H.Th. Jongen, P. Jonker and F. Twilt, Nonlinear Optimization in Finite Dimensions, Kluwer, 2000.
- O. Stein, Bi-Level Strategies in Semi-infinite Programming, Kluwer, 2003.
- C. Roos, T. Terlaky, J.-P. Vial, Interior Point Approach to Linear Optimization: Theory and Algorithms, John Wiley and Sons, 1998.
- A.M. Rubinov, Abstract Convexity and Global Optimization, Kluwer Academic Publishers, 2000.
- G.-W. Weber, Generalized Semi-Infinite Optimization and Related Topics, Heldermann, 2003.
Furthermore, there will be Lecture Notes distributed which are prepared by the guests who we will have at IAM in the semester: Prof. Dr. Georg Still (Enschede, NL), Prof. Dr. Ronald Hoppe (Augsburg, Germany), Prof. Dr. Stef Tijs (Tilburg, NL) and Prof. Dr. Zeev Volkovich (Karmiel, Israel).
The special character of the course is coming from both renowned experts being at IAM as guests and lecturing (cf. attachment), and also the participants – our “young colleagues” – preparing and presenting. Laboratory: Will be arranged if ever being needed.
- MATLAB 6.1
Outline
- 1. Week: Parametric optimization
- 2. Week: Parametric optimization
- 3. Week: Parametric optimization
- 4. Week: Line search methods, trust region methods and derivative free optimization
- 5. Week: Conic and semidefinite optimization
- 6. Week: Interior point methods
- 7. Week: Game theory
- 8. Week: Game theory
- 9. Week: Semi-infinite optimization
- 10. Week: Semi-infinite optimization
- 11. Week: Constrained PDE optimization
- 12. Week: Constrained PDE optimization
- 13. Week: Constrained PDE optimization
- 14. Week: Continuous optimization in clustering theory
- 15. Week: Continuous optimization in clustering theory
- 16. Week: Continuous optimization in clustering theory
- 17. Week: Conclusion, outlook and report finalization
Depending on the times of stay of our four international guests at IAM, the sequence of the contents can change.
First Meeting
First Meeting (and Lecture / Exercise)
Friday, February 20, 9.40-12.30 IAM Building (S-209)