Course Name | Discrete Optimization |
Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
---|---|---|---|---|---|
IE 510 | Fall/Spring | 3 | 0 | 3 | 7.5 |
Prerequisites | None | |||||
Course Language | English | |||||
Course Type | Elective | |||||
Course Level | Second Cycle | |||||
Mode of Delivery | - | |||||
Teaching Methods and Techniques of the Course | ||||||
Course Coordinator | - | |||||
Course Lecturer(s) | - | |||||
Assistant(s) | - |
Course Objectives | Purpose of this course is to give the students an understanding and experience about discrete optimizaton problems, related concepts and exact and approximate solution techniques. |
Learning Outcomes | The students who succeeded in this course;
|
Course Description | Topics of this course include optimality, relaxation, bounds, network flow problems, branch and bound, dynamic programming, cutting planes and approximation algorithms. |
Related Sustainable Development Goals | |
| Core Courses | |
Major Area Courses | X | |
Supportive Courses | ||
Media and Managment Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Required Materials |
1 | Introduction | |
2 | Optimality, Relaxation and Bounds | |
3 | Optimality, Relaxation and Bounds | |
4 | Well-solved Cases: Network Flows, Shortest Path, Optimal Trees, Matching and Assignments | |
5 | Well-solved Cases: Network Flows, Shortest Path, Optimal Trees, Matching and Assignments | |
6 | Branch and Bound Methods | |
7 | Branch and Bound Methods | |
8 | Midterm exam | |
9 | Cutting Plane Algorithms: Valid Inequalities, Theory and Practice | |
10 | Cutting Plane Algorithms: Valid Inequalities, Theory and Practice | |
11 | Cutting Plane Algorithms: Valid Inequalities, Theory and Practice | |
12 | Dynamic Programming | |
13 | Approximation Algorithms | |
14 | Approximation Algorithms | |
15 | General Review and Evaluation | |
16 | General Review and Evaluation |
Course Notes/Textbooks | Instructor notes and lecture slides |
Suggested Readings/Materials | Integer Programming. Laurence A. Wolsey, Wiley, 1998.\nInteger and Combinatorial Optimization. Laurence A. Wolsey, George L. Nemhauser, Wiley, 1999.\nApplied Integer Programming: Modeling and Solution, Der-San Chen, Robert G. Batson, Yu Dang, Wiley, 2010. |
Semester Activities | Number | Weigthing |
Participation | 1 | 10 |
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | | |
Portfolio | ||
Homework / Assignments | 1 | 20 |
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exam | ||
Midterm | 1 | 30 |
Final Exam | 1 | 40 |
Total |
Weighting of Semester Activities on the Final Grade | 60 | |
Weighting of End-of-Semester Activities on the Final Grade | 40 | |
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 | 15 | 4 | 60 |
Field Work | |||
Quizzes / Studio Critiques | | ||
Portfolio | |||
Homework / Assignments | 4 | 15 | |
Presentation / Jury | |||
Project | |||
Seminar / Workshop | |||
Oral Exam | |||
Midterms | 1 | 27 | |
Final Exams | 1 | 30 | |
Total | 225 |
# | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
1 | To have an appropriate knowledge of methodological and practical elements of the basic sciences and to be able to apply this knowledge in order to describe engineering-related problems in the context of industrial systems. | X | ||||
2 | To be able to identify, formulate and solve Industrial Engineering-related problems by using state-of-the-art methods, techniques and equipment. | X | ||||
3 | To be able to use techniques and tools for analyzing and designing industrial systems with a commitment to quality. | X | ||||
4 | To be able to conduct basic research and write and publish articles in related conferences and journals. | X | ||||
5 | To be able to carry out tests to measure the performance of industrial systems, analyze and interpret the subsequent results. | X | ||||
6 | To be able to manage decision-making processes in industrial systems. | X | ||||
7 | To have an aptitude for life-long learning; to be aware of new and upcoming applications in the field and to be able to learn them whenever necessary. | X | ||||
8 | To have the scientific and ethical values within the society in the collection, interpretation, dissemination, containment and use of the necessary technologies related to Industrial Engineering. | X | ||||
9 | To be able to design and implement studies based on theory, experiments and modeling; to be able to analyze and resolve the complex problems that arise in this process; to be able to prepare an original thesis that comply with Industrial Engineering criteria. | X | ||||
10 | To be able to follow information about Industrial Engineering in a foreign language; to be able to present the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. | X |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest