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IE 357 | Course Introduction and Application Information
| Course Name |
Special Topics in Optimization
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 357
|
FALL
|
3
|
0
|
3
|
6
|
| Prerequisites | IE 252 To be successful (To have received at least DD grade) | |||||
| Course Language | English | |||||
| Course Type | ELECTIVE_COURSE | |||||
| Course Level | First Cycle | |||||
| Mode of Delivery | Face-To-Face | |||||
| Teaching Methods and Techniques of the Course | Lecture / Presentation | |||||
| National Occupational Classification Code | - | |||||
| Course Coordinator |
|
|||||
| Course Lecturer(s) |
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|||||
| Assistant(s) | - | |||||
| Course Objectives | This course aims to teach advanced solution techniques and algorithms for large-scale integer programming problems. It covers methods such as linear programming relaxations, Dantzig-Wolfe decomposition, branch-and-bound algorithm, Lagrangian relaxation, cutting plane methods, Benders decomposition, and dynamic programming. The course seeks to provide students with a comprehensive understanding of the theoretical foundations and practical applications of these techniques. | |||||||||||||||||||||||||||||||||||||||||||||
| Learning Outcomes |
The students who succeeded in this course;
|
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| Course Description | Classical Optimization Methods, Linear Programming Relaxation, Dantzig-Wolfe Decomposition, Branch-and-Bound Algorithm, Lagrangian Relaxation, Cutting Plane Method, Benders Decomposition | |||||||||||||||||||||||||||||||||||||||||||||
| Related Sustainable Development Goals |
-
|
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|
|
Core Courses |
|
| Major Area Courses |
X
|
|
| Supportive Courses |
|
|
| Media and Managment Skills Courses |
|
|
| Transferable Skill Courses |
|
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Required Materials | Learning Outcome |
| 1 | Review of Optimization Fundamentals | Lecture Notes | LO1 |
| 2 | Solution Methods for Large-Scale Integer Programming Problems: Linear Programming Relaxations | Lecture Notes | LO2 |
| 3 | Solution Methods for Large-Scale Integer Programming Problems: Dantzig&Wolfe Algorithm | Lecture Notes | LO3 |
| 4 | Solution Methods for Large-Scale Integer Programming Problems: Branch and Bound Algorithm | Lecture Notes | LO3 |
| 5 | Solution Methods for Large-Scale Integer Programming Problems: Branch and Bound Algorithm | Lecture Notes | LO3 |
| 6 | Solution Methods for Large-Scale Integer Programming Problems: Lagrangian Relaxation | Lecture Notes | LO3 |
| 7 | Solution Methods for Large-Scale Integer Programming Problems: Lagrangian Relaxation | Lecture Notes | LO3 |
| 8 | Midterm Exam | - | |
| 9 | Solution Methods for Large-Scale Integer Programming Problems: Branch and Cut Algorithm | Lecture Notes | LO3 |
| 10 | Solution Methods for Large-Scale Integer Programming Problems: Cutting Plane Algorithm | Lecture Notes | LO3 |
| 11 | Solution Methods for Large-Scale Integer Programming Problems: Benders Decomposition | Lecture Notes | LO4 |
| 12 | Midterm | - | |
| 13 | Dynamic Programming | Lecture Notes | LO4 |
| 14 | Dynamic Programming | Lecture Notes | LO4 |
| 15 | Review | - | |
| 16 | Final Exam | - |
| Course Notes/Textbooks | Wolsey L. A. and Nemhauser G. L. (2014). Integer and combinatorial optimization. John Wiley and Sons. |
| Suggested Readings/Materials | Martin R. K. (2012) Large scale linear and integer optimization a unified approach. Springer Science and Business Media. |
EVALUATION SYSTEM
| Semester Activities | Number | Weighting | LO1 | LO2 | LO3 | LO4 |
| Midterm | 2 | 60 | X | X | X | X |
| Final Exam | 1 | 40 | X | X | X | X |
| Total | 3 | 100 |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Participation | - | - | - |
| Theoretical Course Hours | 16 | 3 | 48 |
| Laboratory / Application Hours | 14 | 4 | 56 |
| Study Hours Out of Class | - | - | - |
| Field Work | - | - | - |
| Quizzes / Studio Critiques | - | - | - |
| Portfolio | - | - | - |
| Homework / Assignments | - | - | - |
| Presentation / Jury | - | - | - |
| Project | - | - | - |
| Seminar / Workshop | - | - | - |
| Oral Exams | - | - | - |
| Midterms | 2 | 22 | 44 |
| Final Exam | 1 | 32 | 32 |
| Total | 180 |
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
| # | PC Sub | Program Competencies/Outcomes | * Contribution Level | ||||
| 1 | 2 | 3 | 4 | 5 | |||
| No program competency data found. | |||||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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