Heuristic Optimization Techniques
Information Systems Engineering
Institute of Natural and Applied Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Heuristic Optimization Techniques | BTM517 | Elective | Master's degree | 1 | Fall | 8 |
Name of Lecturer(s)
Prof. Dr. Mehmet YILDIRIM
Research Assistant Seda BALTA
Research Assistant Gizem YILDIZ
Learning Outcomes of the Course Unit
1) Explain the basic concepts in heuristic optimization
2) Classify the optimization problems and solution techniques
3) Compare the heuristic search and optimization algorithms
4) Implement the heuristic algorithms in optimization problems
5) Solve the constrained optimization problems
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | ||
| Learning Outcomes | ||||||||
| 1 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 2 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | No relation | No relation | No relation | High | No relation | No relation | No relation | |
| 4 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 5 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Matlab, Phyton, C++
Course Contents
Basic concepts in heuristic optimizations: description of problem, representation, cost function, local and global optima, neighborhood, hill climbing. Classification of optimization problems and their solution techniques. Consideration of constraints. Heuristic search and optimization algorithms: constructive search, local search, simulated annealing, tabu search, genetic algorithms, ant colony optimization, artificial neural network and hybrid algorithms.
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Not Required