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 | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | 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 | Nonlinear programming examples in real life. Partial-order derivatives and Taylor series expansion. | [1] pages 610—618 |
| 2 | Local and global optimum. Convexity. | [1] pages 619—636 |
| 3 | Line search and unconstrained optimization. | [1] pages 637—660 |
| 4 | Constrained optimization. Lagrange multipliers. Optimality conditions. | [1] pages 663—679 |
| 5 | Deterministic inventory models. Economic order quantity (EOQ) model with finite production rate and backorders. | [1] pages 846—858, 865—872 |
| 6 | EOQ models with quantity discounts. | [1] pages 859—865 |
| 7 | Midterm I | |
| 8 | Multi-item EOQ models. | [1] pages 873—876 |
| 9 | Probabilistic inventory models. Reorder point models with uncertain demand. | [1] pages 890—906 |
| 10 | Decision making and utility functions. | [1] pages 737—772 |
| 11 | Decision making and utility functions. | [1] pages 737—772 |
| 12 | Analytic hierarchy process for decision making with multiple objectives Midterm II | [1] pages 785—793 |
| 13 | [1] pages 785—793 Dynamic programming approach. Solution of the knapsack problem with dynamic programming. | [1] pages 961—968, 974—984 |
| 14 | Dynamic lot-sizing problems and the Wagner-Whitin algorithm. | [1] pages 1001—1013 |
| 15 | Probabilistic inventory problems with dynamic programming. | [1] pages 1016—1029 |
| 16 | Final Examination Period |
Sources
| Course Book | 1. W.L. Winston, Operations Research (4th ed.), Duxbury, 2004. |
|---|---|
| Other Sources | 2. F.S. Hillier and G.J. Lieberman, Introduction to Operations Research (8th ed.), McGraw-Hill, 2005. |
| 3. H. A. Taha, Operations Research: An Introduction (8th ed.), Prentice-Hall, 2006. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 3 | 15 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 6 | 100 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| 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 | Gains the ability to apply the acquired knowledge in mathematics, science and engineering. | |||||
| 2 | Gains the ability to identify, formulate and solve complex engineering problems | X | ||||
| 3 | Gains the ability to accomplish the integration of systems. | |||||
| 4 | Gains the ability to design, develop, implement and improve complex systems, components, or processes. | |||||
| 5 | Acquires the ability to select,develop and use suitable modern engineering techniques and tools. | X | ||||
| 6 | Gains the ability to design/conduct experiments and collect, analyze, and interpret data. | |||||
| 7 | Gains the ability to function independently and in teams. | |||||
| 8 | Gains the ability to make use of oral and written communication skills effectively. | |||||
| 9 | Gains the ability to recognize the need for and engage in life-long learning. | |||||
| 10 | Attains the ability to understand and exercise professional and ethical responsibility. | |||||
| 11 | Gains the ability to understand the impact of engineering solutions. | |||||
| 12 | Cultivates the ability to have knowledge of contemporary issues. | |||||
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 | 2 | 20 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 3 | 6 | 18 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 10 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 19 | 19 |
| Total Workload | 125 | ||