ECTS - Heuristic Methods
Heuristic Methods (IE511) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Heuristic Methods | IE511 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Technical Elective Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| 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 | |
|---|---|
| Major Area Courses | |
| Supportive Courses | X |
| 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 apply the acquired knowledge in mathematics, science and engineering | X | ||||
| 2 | Ability to identify, formulate and solve complex engineering problems | X | ||||
| 3 | Ability to accomplish the integration of systems | X | ||||
| 4 | Ability to design, develop, implement and improve complex systems, components, or processes | X | ||||
| 5 | Ability to select/develop and use suitable modern engineering techniques and tools | X | ||||
| 6 | Ability to design/conduct experiments and collect/analyze/interpret data | X | ||||
| 7 | Ability to function independently and in teams | X | ||||
| 8 | Ability to make use of oral and written communication skills effectively | X | ||||
| 9 | Ability to recognize the need for and engage in life-long learning | X | ||||
| 10 | Ability to understand and exercise professional and ethical responsibility | X | ||||
| 11 | Ability to understand the impact of engineering solutions | X | ||||
| 12 | Ability to have knowledge of contemporary issues | X | ||||
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 | ||