HEURISTICS METHODS for OPTIMIZATION

AIM

To give an introduction to the heuristic techniques which can be used to solve optimization problems. A set of heuristic algorithms together with their practical applications to system design will be discussed.

CONTENT

This course contains; Introduction to combinatorial optimization problems.,Introduction to combinatorial optimization problems., Basic principles of heuristic techniques.,Heuristic techniques,Heuristic techniques,Heuristic techniques,Yakınsama ve uydurma,Geometric problems,Geometric problems,Unconstrained minimization,Unconstrained minimization,Equality constrained minimization,Stochastic combinatorial optimization.,Case studies.

1. 1

   Will learn Basic principles of heuristic techniques.

   Taught by: Problem Solving Method, Self Study Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

2. 2

   Will learn about the applications of heuristic techniques.

   Taught by: Problem Solving Method, Self Study Method, Question - Answer Technique, Project Based Learning Model, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

WEEKLY PLAN

1. WEEK 1

   Introduction to combinatorial optimization problems.

   Preparation: Presentation PDF of the Week

2. WEEK 2

   Introduction to combinatorial optimization problems.

   Preparation: Presentation PDF of the Week

3. WEEK 3

   Basic principles of heuristic techniques.

   Preparation: Presentation PDF of the Week

4. WEEK 4

   Heuristic techniques

   Preparation: Presentation PDF of the Week

5. WEEK 5

   Heuristic techniques

   Preparation: Presentation PDF of the Week

6. WEEK 6

   Heuristic techniques

   Preparation: Presentation PDF of the Week

7. WEEK 7

   Yakınsama ve uydurma

   Preparation: Presentation PDF of the Week

8. WEEK 8

   Geometric problems

   Preparation: Presentation PDF of the Week

9. WEEK 9

   Geometric problems

   Preparation: Presentation PDF of the Week

10. WEEK 10

    Unconstrained minimization

    Preparation: Presentation PDF of the Week

11. WEEK 11

    Unconstrained minimization

    Preparation: Presentation PDF of the Week

12. WEEK 12

    Equality constrained minimization

    Preparation: Presentation PDF of the Week

13. WEEK 13

    Stochastic combinatorial optimization.

    Preparation: Presentation PDF of the Week

14. WEEK 14

    Case studies

    Preparation: Overall examination of the provided case studies.

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

READING

• Heuristics for Optimization and Learning, Yalaoui, Farouk, Amodeo, Lionel, Talbi, El-Ghazali , Springer
• Convex Optimization; S. Boyd, L.Vandenberghe, Cambridge university press, 2004; Reeves CR (1995) Modern heuristic techniques for combinatorial problems. McGraw-Hill, Londres

TEACHING STAFF

• Lect.Dr. Esin TETİKCOORDINATOR
• Prof.Dr. Hakan TOZAN