ECTS - Heuristic Methods
Heuristic Methods (IE511) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Heuristic Methods | IE511 | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Ph.D. |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | The course aims to teach students fundamental concepts of heuristic models to apply to real-life problems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | The background of heuristic applications for search methods for optimization purposes and the possible application areas, complex optimization problems and possible solving strategies using heuristic algorithms, heuristic search methods, simulated annealing, taboo search general structure, algorithms, application areas, neural networks, general str |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | The background of heuristic applications for search methods for optimization purposes, the possible application areas. | |
| 2 | Complex optimization problems and possible solving strategies using heuristic algorithms. | |
| 3 | Heuristic search methods. | |
| 4 | Simulated Annealing: general structure, application areas, development of algorithms specific to problems. | |
| 5 | Taboo Search: general structure, application areas, development of algorithms specific to problems. | |
| 6 | Neural networks: general structure, application areas, development of algorithms specific to problems. | |
| 7 | Midterm | |
| 8 | Discrete and continuous applications. | |
| 9 | Discrete and continuous applications. | |
| 10 | Advantages and disadvantages of heuristic search methods for both series and parallel computation in comparison to other optimization algorithms. | |
| 11 | Practical applications, real life problems | |
| 12 | Practical applications, real life problems | |
| 13 | Implementation and term project | |
| 14 | Implementation and term project | |
| 15 | Implementation and term project | |
| 16 | Final Examination Period |
Sources
| Course Book | 1. G. Polya, How to Solve It: A New Aspect of Mathematical Method, Ishi Press, 2009. |
|---|---|
| Other Sources | 2. S. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, 2009. |
| 3. Reeves,C. Modern Heuristic Techniques for Combinatorial Problems,Halsted Press, 2003. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 1 | 30 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 3 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Ability to carry out advanced research activities, both individual and as a member of a team | |||||
| 2 | Ability to evaluate research topics and comment with scientific reasoning | |||||
| 3 | Ability to initiate and create new methodologies, implement them on novel research areas and topics | |||||
| 4 | Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions | |||||
| 5 | Ability to apply scientific philosophy on analysis, modelling and design of engineering systems | |||||
| 6 | Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level | |||||
| 7 | Contribute scientific and technological advancements on engineering domain of his/her interest area | |||||
| 8 | Contribute industrial and scientific advancements to improve the society through research activities | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 1 | 16 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 4 | 4 |
| Report | |||
| Homework Assignments | 4 | 4 | 16 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 16 | 16 |
| Prepration of Final Exams/Final Jury | 1 | 25 | 25 |
| Total Workload | 125 | ||