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 | Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area | |||||
| 2 | Can apply gained knowledge and problem solving abilities in inter-disciplinary research | |||||
| 3 | Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary | |||||
| 4 | Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study | |||||
| 5 | Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework | |||||
| 6 | Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility | |||||
| 7 | Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation | |||||
| 8 | To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2) | |||||
| 9 | Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge | |||||
| 10 | Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach. | |||||
| 11 | Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications. | |||||
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 | ||