Course Name | Heuristics in Optimization |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
IE 358 | Fall/Spring | 3 | 0 | 3 | 6 |
Prerequisites |
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Course Language | English | ||||||||
Course Type | Elective | ||||||||
Course Level | First Cycle | ||||||||
Mode of Delivery | - | ||||||||
Teaching Methods and Techniques of the Course | Lecturing / Presentation | ||||||||
Course Coordinator | |||||||||
Course Lecturer(s) | |||||||||
Assistant(s) | - |
Course Objectives | The purpose of this course is to fundamental concepts of heuristics in solving various optimization problems with emphasis on metaheuristics |
Learning Outcomes | The students who succeeded in this course;
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Course Description | This course introduces the concept of heuristics to students who already know about mathematical optimization. The topics include basic heuristic constructs (greedy, improvement, construction); meta heuristics such as simulated annealing, tabu search, genetic algorithms, ant algorithms and their hybrids. The basic material on the heuristic will be covered in regular lectures The students will be required to present a variety of application papers on different subjects related to the course. In addition, as a project assignment the students will design a heuristic, write a code of an appropriate algorithm for the problem and evaluate its performance. |
Related Sustainable Development Goals | |
| Core Courses | |
Major Area Courses | ||
Supportive Courses | ||
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Reminder for Optimization | Reading: Textbook (Michalewicz) introduction Ch 1 |
2 | Introduction to complexity and heuristics | Lecture notes/slides provided |
3 | Simulated Annealing | Lecture notes/ slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 8 |
4 | Particle Swarm Optimization | Lecture notes/slides provided |
5 | Genetic Algorithms and Evolutionary Strategies 1 | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 3 |
6 | Genetic Algorithms and Evolutionary Strategies 1 | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 3 |
7 | MIDTERM | |
8 | Ant Colony Optimization | Lecture notes/slides provided, Reading: Handbook of Metaheuristics Ch 9 |
9 | Tabu Search | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 2 |
10 | Tabu Search | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 2 |
11 | GRASP | Lecture notes/slides provided Handbook of Metaheuristics Ch 8 |
12 | Scatter Search | Lecture notes/slides provided Handbook of Metaheuristics Ch 1 |
13 | Local Search 1 | Lecture notes/slides provided Handbook of Metaheuristics Ch 11 |
14 | Local Search 2 Neighbourhoods, VNS | Lecture notes/slides provided Reading: Handbook of MetaheuristicsCh 6 |
15 | Review of Final | Lecture notes/slides provided |
16 | Review of the Semester |
Course Notes/Textbooks | Textbook:Zbigniew Michalewicz, David B. Fogel “How to Solve It: Modern Heuristics |
Suggested Readings/Materials | "Handbook of Metaheuristics" edt by: Glover F.,, Kochenberger G.A., Kluwer, 2003 and Lecture PowerPoint slides |
Semester Activities | Number | Weigthing |
Participation | 1 | 5 |
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments | 5 | 20 |
Presentation / Jury | ||
Project | 1 | 35 |
Seminar / Workshop | ||
Oral Exam | ||
Midterm | 1 | 20 |
Final Exam | 1 | 20 |
Total |
Weighting of Semester Activities on the Final Grade | 8 | 80 |
Weighting of End-of-Semester Activities on the Final Grade | 1 | 20 |
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
Study Hours Out of Class | 14 | 5 | 70 |
Field Work | |||
Quizzes / Studio Critiques | |||
Portfolio | |||
Homework / Assignments | 5 | 3 | |
Presentation / Jury | |||
Project | 1 | 17 | |
Seminar / Workshop | |||
Oral Exam | |||
Midterms | 1 | 10 | |
Final Exams | 1 | 20 | |
Total | 180 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To have adequate knowledge in Mathematics, Science and Computer Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems. | |||||
2 | To be able to identify, define, formulate, and solve complex Computer Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose. | |||||
3 | To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose. | |||||
4 | To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Computer Engineering applications; to be able to use information technologies effectively. | |||||
5 | To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Computer Engineering research topics. | |||||
6 | To be able to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; to be able to work individually. | |||||
7 | To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions. | |||||
8 | To have knowledge about global and social impact of Computer Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Computer Engineering solutions. | |||||
9 | To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications. | |||||
10 | To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. | |||||
11 | To be able to collect data in the area of Computer Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1) | |||||
12 | To be able to speak a second foreign language at a medium level of fluency efficiently. | |||||
13 | To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Computer Engineering. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest