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 | 3 | 2 | 0 | 4 | 8 |
| Pre-requisite Course(s) |
|---|
| IE 222 |
| Course Language | English |
|---|---|
| Course Type | N/A |
| 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 | An ability to apply knowledge of mathematics, science and engineering to Industrial Engineering; an ability to apply theoretical and practical knowledge to model and solve engineering problems. | X | ||||
| 2 | An ability to identify, formulate and solve complex engineering problems; an ability to select and apply proper analysis and modeling methods. | X | ||||
| 3 | An ability to design a complex system, process, tool or component to meet desired needs within realistic constraints; an ability to apply modern design. | |||||
| 4 | An ability to develop, select and put into practice techniques, skills and modern engineering tools necessary for engineering practice; an ability to use information technology effectively. | X | ||||
| 5 | An ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or disciplinary research topics. | |||||
| 6 | An ability to work individually, on teams, and/or on multidisciplinary teams. | |||||
| 7 | Ability to communicate effectively in Turkish orally and in writing; knowledge of at least one foreign language; effective report writing and understand written reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instruction. | |||||
| 8 | A recognition of the need for, and an ability to engage in life-long learning; an ability to use information-seeking tools and to follow the improvements in science and technology. | |||||
| 9 | An ability to behave according to the ethical principles, an understanding of professional and ethical responsibility. Information on standards used in industrial engineering applications. | |||||
| 10 | Knowledge of business applications such as project management, risk management and change management. A recognition of entrepreneurship, innovativeness. Knowledge of sustainable improvement. | X | ||||
| 11 | Information on the effects of industrial engineering practices on health, environment and security in universal and societal dimensions and the information on the problems of the in the field of engineering of the era. Awareness of the legal consequences of engineering solutions. | |||||
| 12 | An ability to design, development, implementation and improvement of integrated systems that include human, materials, information, equipment and energy. | X | ||||
| 13 | Knowlede on appropriate analytical, computational and experimental methods to provide 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 | ||