GRADUATE SCHOOL
Ph.D. In Electrical-Electronics Engineering
IES 538 | Course Introduction and Application Information
| Course Name |
Nature Inspired Optimization
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IES 538
|
Fall/Spring
|
3
|
0
|
3
|
7.5
|
| Prerequisites |
None
|
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| Course Language |
English
|
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| Course Type |
Elective
|
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| Course Level |
Second Cycle
|
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| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | - | |||||
| Course Coordinator | - | |||||
| Course Lecturer(s) | - | |||||
| Assistant(s) | - | |||||
| Course Objectives | The purpose of this course is to introduce natureinspired optimisation techniques and show how these techniques can be used. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | This course introduces a range of natureinspired algorithms for both realvalued and combinatorial optimisation. Examples of such algorithms include: Evolutionary Algorithms, Ant Colony Algorithms, Simulated Annealing, Tabu Search. The study of these techniques and the problems for which they are designed will take place within the broader context of established optimisation theory. Such theory as currently exists for the new techniques will also be presented. |
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Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Combinatorial optimisation – introduction to problems and algorithms / Kombinatoryel optimization –problem ve algoritmalara giriş | |
| 2 | Local search algorithms / Yerel arama algoritmaları | |
| 3 | Simulated annealing / Benzetilmiş Tavlama | |
| 4 | Genetic algorithms / Genetik Algoritmalar | |
| 5 | Ant colony optimisation / Karınca Kolonisi Algoritması | |
| 6 | Tabu search /Tabu Araması | |
| 7 | Hybrid methods / Hibrid Yöntemler | |
| 8 | Hybrid methods / Hibrid Yöntemler | |
| 9 | Real valued optimization / Gerçek değerli optimizasyon | |
| 10 | Evolutionary strategies / Evrimsel Stratejiler | |
| 11 | Evolutionary strategies / Evrimsel Stratejiler | |
| 12 | Gray code algorithms /Gri kod algoritmalar | |
| 13 | CHC / CHC | |
| 14 | No Free Lunch / No Free Lunch Teoremi | |
| 15 | Review and presentations / Tekrar ve sunumlar | |
| 16 | Review of the Semester |
| Course Notes/Textbooks | Yukarıda belirtilen kitap ve ders yansıları / The textbook referenced above and course slides |
| Suggested Readings/Materials | Modern Heuristic Techniques for Combinatorial Problems C Reeves McGrawHill, 1995 How To Solve It Z Michalewicz & D B Fogel Springer, 2000 Stochastic Local Search H Hoos & T Stuzle Elsevier, 2005 New Ideas in Optimization D Corne, M Dorigo & F Glover McGrawHill, 1999İlgili Araştırma Makaleleri / Related Research Papers |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation |
5
|
|
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments |
5
|
20
|
| Presentation / Jury | ||
| Project |
1
|
35
|
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
20
|
| Final Exam |
1
|
20
|
| Total |
| Weighting of Semester Activities on the Final Grade |
80
|
|
| Weighting of End-of-Semester Activities on the Final Grade |
40
|
|
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
3
|
48
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
0
|
|
| Study Hours Out of Class |
15
|
4
|
60
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
0
|
||
| Portfolio |
0
|
||
| Homework / Assignments |
5
|
8
|
40
|
| Presentation / Jury |
10
|
0
|
|
| Project |
1
|
40
|
40
|
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
20
|
20
|
| Final Exam |
1
|
22
|
22
|
| Total |
230
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
||
| 1 | Accesses information in breadth and depth by conducting scientific research in Electrical and Electronics Engineering; evaluates, interprets and applies information. | |||||
| 2 | Is well-informed about contemporary techniques and methods used in Electrical and Electronics Engineering and their limitations. | |||||
| 3 | Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines. Knows and applies the research methods in studies of the area with a high level of skill. |
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| 4 | Is informed about new and upcoming applications in the field and learns them whenever necessary. | |||||
| 5 | Defines and formulates problems related to Electrical and Electronics Engineering, develops methods to solve them and uses progressive methods in solutions. Can independently realize novel studies that bring innovation to the field, or methods, or design, or known methods. |
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| 6 | Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs. | |||||
| 7 | Designs and implements studies based on theory, experiments and modeling; analyses and resolves the complex problems that arise in this process. Performs critical analysis, synthesis and evaluation of new and complex ideas. | |||||
| 8 | Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility. | |||||
| 9 | Engages in written and oral communication at least in Level C1 of the European Language Portfolio Global Scale. | |||||
| 10 | Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. |
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| 11 | Evaluates the results of scientific, technological and engineering research and development activities in terms of the social, environmental, health, safety and legal aspects. Examines social relations and norms related to the field, and develops and makes attempts to change them if necessary. Knows their project management and business applications, and is aware of their limitations in Electrical and Electronics Engineering applications. |
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| 12 | Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. Adheres to the principles of research and publication ethics. |
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*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest