| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Optimization Techniques | YZM326 | Elective | Bachelor's degree | 3 | Spring | 5 |
Name of Lecturer(s)
Prof. Dr. Kerem KÜÇÜK
Learning Outcomes of the Course Unit
1) Comprehend the concepts of optimization theory
2) Comprehend the gradient based algorithms
3) Comprehend constraint optimization
4) learn dynamic optmization concept
5) Being equipped with advanced knowledge on optimaization theory such as; heuristic optimization
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
| Learning Outcomes | |||||||||||||
| 1 | High | High | Middle | High | High | Middle | High | Middle | Low | Middle | Middle | Low | |
| 2 | Middle | Middle | Middle | High | Low | Middle | Middle | Low | High | Low | High | Low | |
| 3 | High | Low | Low | High | Low | Low | High | Middle | High | High | Middle | Low | |
| 4 | Middle | Low | High | Low | Middle | Low | Low | High | Low | Middle | Middle | Low | |
| 5 | High | Middle | Low | Low | High | Low | Middle | Middle | Middle | High | Middle | Low | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
This course equips candidates with in-depth knowledge on the classification of analitical optimization and techniques, unlimited,linear limited ,nonlinear limited optimization, lagrange multiplier method, Kuhn-Tucker rules,punishment functions,linear,squre and unlinear programing, engineering applications, dynamic optimization and Heuristic optimization
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Not Required