Instructor: Dr Cenk Toker
Monday 09:00-12:00

Course Homepage: http://www.ee.hacettepe.edu.tr/~toker/ELE704/

Course Objective: Optimization is an interdisciplinary mathematical tool which helps you to find an optimum solution to a mathematically modeled problem. During the course you will be given the necessary tools to model and solve an engineering problem as an optimization problem.

Topics to be covered:
Convex Sets, Convex Functions, Convex Optimization Problems, Duality
Approximation and Fitting, Statistical Estimation, Geometric Problems
Unconstraint Optimization, Equality Constrained Optimization, Interior-Point Methods

Prerequisite: Very good knowledge of linear algebra and ability to write a program with moderate complexity in MATLAB.
You must be very good at geometric thinking, and you must also be willing to think and study on the subject given during the lecture at home, possibly spending at least 5-6 hours per lecture apart from the time spend at school.

Textbook: There is no specific textbook. Lecture notes will be a composition of the references below:
1. Luenberger, Linear and Nonlinear Programming, Kluwer, 2002,
2. Boyd and Vandenberghe, Convex Optimization, Cambridge, 2004,
3. Baldick, Applied Optimization, Cambridge, 2006,
4. Freund, Lecture Notes, MIT,
5. Bertsekas, Lecture Notes, MIT,
6. Bertsekas, Nonlinear Programming, Athena Scientific, 1999.

Grading: Midterm exam: 25%, Quiz (5 out of 6) 25%, Final exam: 50%

Lecture Notes: click