ECTS - Operations Research II
Operations Research II (IE323) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Operations Research II | IE323 | 5. Semester | 3 | 2 | 0 | 4 | 8 |
| Pre-requisite Course(s) |
|---|
| IE222 |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Drill and Practice, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | Students should have the ability to model and solve real life problems using operations research techniques and be able to analyze results obtained with such models. Student should understand the different types of models, such as deterministic vs. stochastic. Students should be able to use software to solve such models. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Modeling with integer variables; network models: model formulation, minimal spanning tree, shortest path, maximal flow problems, critical path method and program evaluation review techniques; nonlinear programming. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | A review of basic OR I and Introduction to Integer Programming | [1] pg. 1-413 [1] pg. 475-476 |
| 2 | Introduction to Integer Programming | [1] pg. 475-476 |
| 3 | Formulating (Mixed) Integer Programming Problems | [1] pg. 477-511 |
| 4 | Formulating (Mixed) Integer Programming Problems | [1] pg. 477-511 |
| 5 | Solving Integer Programming Problems-Relationship to Linear Programming-Branch and Bound | [1] pg. 512-544 |
| 6 | Solving Integer Programming Problems-Relationship to Linear Programming-Branch and Bound | [1] pg. 512-544 |
| 7 | Midterm I | |
| 8 | Solving Integer Programming Problems-Implicit Enumeration-Cutting Plane Algorithm | [1] pg. 545-561 |
| 9 | Solving Integer Programming Problems-Implicit Enumeration-Cutting Plane Algorithm History of the Network Models, Terminology and Notation | [1] pg. 545-561 [1] pg. 413-414 |
| 10 | Midterm II Minimum Spanning Tree Problems-Prim’s algorithm, Kruskal’s algorithm | [1] pg. 456-458 |
| 11 | Minimum Spanning Tree Problems-Prim’s algorithm, Kruskal’s algorithm | [1] pg. 456-458 |
| 12 | Shortest Path Problems-Dijkstra’s algorithm | [1] pg. 414-418 |
| 13 | Maximum Flow Problems Ford-Fulkerson Algorithm, Max-flow Min-cut theorem | [1] pg. 419-430 |
| 14 | Maximum Flow Problems Ford-Fulkerson Algorithm, Max-flow Min-cut theorem Project Management, CPM and PERT, Crashing Project, Minimum Cost Network Flow Problems, Network Simplex | [1] pg. 419-430 [1] pg. 431-449 |
| 15 | Project Management, CPM and PERT, Crashing Project, Minimum Cost Network Flow Problems, Network Simplex | [1] pg. 431-449 |
| 16 | Project Management, CPM and PERT, Crashing Project, Minimum Cost Network Flow Problems, Network Simplex Introduction to Nonlinear Programming | [1] pg. 431-449 [1] pg. 610-650 |
Sources
| Course Book | 1. Winston, W.L. Operations Research: Applications and Algorithms, 4rd Edition, Duxbury Press, Belmont, California, USA. |
|---|---|
| Other Sources | 2. Hillier, F.S. and Lieberman, G.J., Introduction to Operations Research, 6th Edition, McGraw-Hill, 1995. |
| 3. Wolsey, L.A., Integer Programming, Wiley-Interscience, 1st Edition, 1998. | |
| 4. Taha, H. A., Operations Research: An Introduction, Prentice Hall, 1996. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | 5 | 20 |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 40 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 8 | 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 | Acquires sufficient knowledge in mathematics, natural sciences, and related engineering disciplines; gains the ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. | X | ||||
| 2 | Gains the ability to identify, define, formulate, and solve complex engineering problems; acquires the skill 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 to meet specific requirements under realistic constraints and conditions, and applies modern design methods for this purpose. | |||||
| 4 | Develops the skills to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in industrial engineering applications; gains the ability to effectively use information technologies. | X | ||||
| 5 | Gains the ability to design experiments, conduct experiments, collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics. | |||||
| 6 | Acquires the ability to work effectively in intra-disciplinary and multidisciplinary teams, as well as individual work skills. | |||||
| 7 | Acquires effective oral and written communication skills in Turkish; at least one foreign language proficiency; gains the ability to write effective reports, understand written reports, prepare design and production reports, make effective presentations, and give and receive clear instructions. | |||||
| 8 | Develops awareness of the necessity of lifelong learning; gains the ability to access information, follow developments in science and technology, and continuously renew oneself. | |||||
| 9 | Acquires the consciousness of adhering to ethical principles, and gains professional and ethical responsibility awareness. Gains knowledge about the standards used in industrial engineering applications. | |||||
| 10 | Gains knowledge about practices in the business life such as project management, risk management, and change management. Develops awareness about entrepreneurship and innovation. Gains knowledge about sustainable development. | X | ||||
| 11 | Gains knowledge about the universal and social dimensions of the impacts of industrial engineering applications on health, environment, and safety, as well as the problems reflected in the engineering field of the era. Gains 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. | X | ||||
| 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 | 16 | 2 | 32 |
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 4 | 64 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | 10 | 1 | 10 |
| Prepration of Midterm Exams/Midterm Jury | 2 | 10 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 26 | 26 |
| Total Workload | 200 | ||