Optimization Methods
Mechatronics Engineering
Faculty of Engineering
First Cycle (Bachelor's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Optimization Methods | MKT227 | Elective | Bachelor's degree | 2 | Fall | 4 |
Name of Lecturer(s)
Prof. Dr. Zafer BİNGÜL
Research Assistant Dr. Haluk ÖZAKYOL
Learning Outcomes of the Course Unit
1) Be able to use optimization methods in mechatronics system design, analysis and control
2) Applying the optimization tools to problems in the field of mechatronics engineering
3) Having knowledge about optimization techniques and applications
4) Learning the optimization concepts
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | |
| 2 | Middle | Middle | Low | Low | Low | Low | Low | Low | Low | Low | Low | |
| 3 | High | High | High | High | High | High | High | High | High | Middle | High | |
| 4 | High | Middle | High | Middle | High | Middle | High | Middle | High | Middle | Middle | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
-
Course Contents
Basic concepts. One and multi-dimensional optimization, constrained and unconstrained optimization, parameter and function optimizations, min-max theorem, lineer and non-lineer programming. Genetic algoriths
Weekly Schedule
1) Definitions and basic concepts related to optimization problem2) Unconstrained optimization methods
3) Line Search Methods
4) Fibonacci, Golden Section Methods
5) Simplex method
6) Curve fitting methods
7) Newton method
8) Quadratic Programming
9) Stepest Descent Methods
10) Conjugate Gradient Methods
11) Davidon-Fletcher-Powell Method
12) Fletcher-Reeves Method
13) constrained optimization methods
14) Multi-objective Optimization
15) Genetic Algorithms
16) Final Week
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Drill and Practice
4) Group Study
5) Simulation
6) Self Study
7) Problem Solving
8) Project Based Learning
Assessment Methods and Criteria
Contribution of Semester Studies to Course Grade |
50% |
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Contribution of Final Examination to Course Grade |
50% |
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Total | 100% | ||||||||||||||
Language of Instruction
Turkish
Work Placement(s)
Not Required