Information Package / Course Catalogue
| Course Code | : EEE533 |
| Course Type | : Area Elective |
| Couse Group | : Second Cycle (Master's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 3 |
| Prt. | : 0 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 6 |
The objective of this course is to understand the essential optimization techniques and apply them to some communication problems.
Unconstrained optimization techniques: Gradient Methods, Newton Methods, Quasi-Newton Methods, Least Squares Analysis, Genetic Algorithms; Linear Programming; Constrained optimization techniques: Convex optimization Problems, Algorithms for constrained optimization.
| 1. | To understand the fundamentals of the optimization problems and solution techniques. |
| 2. | To be able to solve unconstrained optimization problems by using different optimization methods. |
| 3. | To learn linear programming. |
| 4. | To gain experience on the convex optimization problems. |
| 5. | To gain ability to do original research in academia or industry through final projects that are closely related to students’ own research interests. |
| 1. | An Introduction to Optimization (4th Edition), by Edwin K. P. Chong , Stanislaw H. Zak. |
| 2. | S. Boyd and L. Vandenberghe, Convex Optimization ,Cambridge University Press, 2004. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Attending Lectures | 1 | %5 |
| Assignment | 3 | %15 |
| Project | 1 | %10 |
| Final Examination | 1 | %70 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 1 | 3 | 56 |
| Assignment | 3 | 12 | 0 | 36 |
| Project | 1 | 16 | 0 | 16 |
| Individual Work | 14 | 2 | 0 | 28 |
| Final Examination | 1 | 12 | 2 | 14 |
| TOTAL WORKLOAD (hours) | 150 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | |
OÇ-1 | 5 | 4 | 5 | 3 | 5 | 3 | 4 |
OÇ-2 | 5 | 4 | 4 | 3 | 5 | 3 | 4 |
OÇ-3 | 5 | 5 | 4 | 3 | 5 | 3 | 4 |
OÇ-4 | 5 | 4 | 4 | 3 | 5 | 3 | 4 |
OÇ-5 | 5 | 5 | 5 | 5 | 5 | 4 | 5 |