| MATHEMATICS (TURKISH, PHD) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| MAT4062 | Numerical Optimization | Fall | 3 | 0 | 3 | 6 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Prof. Dr. SÜREYYA AKYÜZ |
| Course Objectives: | The objective of this course is to introduce the central ideas behind algorithms for the numerical solution of differentiable optimization problems by presenting key methods for both unconstrained and constrained optimization, as well as providing theoretical justification as to why they succeed. |
|
The students who have succeeded in this course; At the end of this course students should be able to tackle optimization problems of in science, engineering and finance using state of art numerical methods. |
| In this course the solution of unconstrained and constrained optimization problem will be discussed. |
| Week | Subject | Related Preparation | |
| 1) | Fundamentals of unconstrained optimization | ||
| 2) | Newton Methods | ||
| 3) | Line Search Method | ||
| 4) | Trust Region Method | ||
| 5) | Quasi-Newton Methods | ||
| 6) | Nonlinear least squares Problem | ||
| 7) | Theory of constrained optimization | ||
| 8) | Theory of linear programming | ||
| 9) | Simplex Method | ||
| 10) | Interior point methods | ||
| 11) | Interior point methods | ||
| 12) | Penalty and barrier methods | ||
| 13) | Sequential Quadratic Programming | ||
| 14) | Conclusion and outlook on unconstrained and constrained optimization | ||
| Course Notes: | G. Nash and Ariela Sofer, Linear and nonlinear programming, New York : McGraw-Hill, 1996, T57.74 N37 J. Nocedal, S.J. Wright, Numerical Optimization, Springer, 1999, QA 402.5 N62 |
| References: | S. Ulbrich, M. Ulbrich, “Nonlinear Optimization”, Lecture Notes, Department of Mathematics, University of Technology Darmstadt, |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | 14 | % 0 |
| Laboratory | 5 | % 5 |
| Application | % 0 | |
| Field Work | % 0 | |
| Special Course Internship (Work Placement) | % 0 | |
| Quizzes | 2 | % 10 |
| Homework Assignments | % 0 | |
| Presentation | % 0 | |
| Project | % 0 | |
| Seminar | % 0 | |
| Midterms | 2 | % 45 |
| Preliminary Jury | % 0 | |
| Final | 1 | % 40 |
| Paper Submission | % 0 | |
| Jury | % 0 | |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Special Course Internship (Work Placement) | 0 | 0 | 0 |
| Field Work | 0 | 0 | 0 |
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentations / Seminar | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework Assignments | 0 | 0 | 0 |
| Quizzes | 2 | 10 | 20 |
| Preliminary Jury | 0 | 0 | 0 |
| Midterms | 2 | 15 | 30 |
| Paper Submission | 0 | 0 | 0 |
| Jury | 0 | 0 | 0 |
| Final | 1 | 16 | 16 |
| Total Workload | 150 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution |