ECTS - Special Topics in Operations Research
Special Topics in Operations Research (IE417) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Special Topics in Operations Research | IE417 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| IE323 |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Question and Answer, Drill and Practice, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | The objective of this course is to introduce some advanced models of operations research together with sample application areas from the industry. Students also have a chance to make use of basic computer packages to solve problems which fit into these mathematical models. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Application of operations research techniques to a specified problem area. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction and Basic Concepts Overview of Operations Research Introduction to Network Optimization | [Course Book] pp. 1–22 |
| 2 | Graph Theory and Network Models Fundamental concepts in graph theory Directed and undirected graphs, network models | [Course Book] pp. 23–52 |
| 3 | Minimum Spanning Tree Overview of minimum spanning tree problems Kruskal's algorithm Prim's algorithm Sollin's algorithm Minimum Spanning Tree and Linear Programming | [Course Book] pp. 510–542 |
| 4 | Shortest Path Problems Overview of shortest path problems Bellman-Ford algorithm Dijkstra's algorithm Floyd-Warshall algorithm Shortest path problems and Linear Programming | [Course Book] pp. 93–165 |
| 5 | Transportation Problems Balanced transportation problems Unbalanced transportation problems Transportation Problems and Linear Programming | [Bazaraa et al., 2011] pp. 513–535 |
| 6 | Assignment Problems Definition of assignment problems Hungarian algorithm | [Course Book] pp. 461–509 |
| 7 | Midterm Exam | |
| 8 | Travelling Salesman Problem (TSP) Definition of TSP Solution algorithms TSP and linear programming | [Bazaraa et al., 2011] pp. 453–512 GAMS |
| 9 | Vehicle Routing Problems (VRP) Problem definition and notation Basic models and formulations | [Toth & Vigo, 2014] pp. 1–28 GAMS |
| 10 | Araç rotalama problemleri (VRP) VRP türleri Çözüm yöntemleri ve yaklaşımlar | [Toth & Vigo, 2014] s. 29–81 GAMS |
| 11 | Facility Location Problem definition and notation Basic models and formulations | [Course Book] pp. 744–748 GAMS |
| 12 | Facility Location Continued exploration of variant models | [Course Book] pp. 744–748 GAMS |
| 13 | Applications and Case Studies Real-world applications in logistics and transportation Case studies analysis | GAMS |
| 14 | Applications and Case Studies Continued discussion on applications and case studies Course review and future research directions | GAMS |
| 15 | Final Examination Period | |
| 16 | Final Exam |
Sources
| Course Book | 1. Ahuja, R. K., Magnanti, T. L., & Orlin, J. B. (1995). Network flows: theory, algorithms and applications. Prentice hall. |
|---|---|
| Other Sources | 2. Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications. Society for industrial and applied mathematics. |
| 3. Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D. (2011). Linear programming and network flows. John Wiley & Sons. | |
| 4. GAMS The General Algebraic Modeling Language |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | 1 | 10 |
| Homework Assignments | 1 | 10 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 35 |
| Final Exam/Final Jury | 1 | 45 |
| Toplam | 4 | 100 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| Major Area Courses | X |
| 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 | Gains adequate knowledge in mathematics, science, and relevant engineering disciplines and acquires the ability to use theoretical and applied knowledge in these fields to solve complex engineering problems. | |||||
| 2 | Gains the ability to identify, formulate, and solve complex engineering problems and the ability to select and apply appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Gains the ability to design a complex system, process, device, or product under realistic constraints and conditions to meet specific requirements and to apply modern design methods for this purpose. | |||||
| 4 | Gains the ability to select and use modern techniques and tools necessary for the analysis and solution of complex engineering problems encountered in industrial engineering applications and the ability to use information technologies effectively. | X | ||||
| 5 | Gains the ability to design experiments, conduct experiments, collect data, analyze results, and interpret findings for investigating complex engineering problems or discipline specific research questions. | |||||
| 6 | Gains the ability to work effectively in intra-disciplinary and multi-disciplinary teams and the ability to work individually. | |||||
| 7 | Gains the ability to communicate effectively in written and oral form, acquires proficiency in at least one foreign language, the ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Gains awareness of the need for lifelong learning and the ability to access information, follow developments in science and technology, and to continue to educate him/herself. | |||||
| 9 | Gains knowledge about behaviour in accordance with ethical principles, professional and ethical responsibility and standards used in industrial engineering applications | |||||
| 10 | Gains knowledge about business practices such as project management, risk management, and change management and develops awareness of entrepreneurship, innovation, and sustainable development. | |||||
| 11 | Gains knowledge about the global and social effects of industrial engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | |||||
| 12 | Gains skills in the design, development, implementation, and improvement of integrated systems involving human, material, information, equipment, and energy. | |||||
| 13 | Gains knowledge about appropriate analytical and experimental methods, as well as computational methods, for ensuring system integration. | |||||
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 | 10 | 3 | 30 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 1 | 8 | 8 |
| Quizzes/Studio Critics | 1 | 8 | 8 |
| Prepration of Midterm Exams/Midterm Jury | 1 | 12 | 12 |
| Prepration of Final Exams/Final Jury | 1 | 19 | 19 |
| Total Workload | 125 | ||