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) |
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N/A |
Course Language | English |
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Course Type | Elective 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 | 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 |
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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. |
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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 |
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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 |
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Percentage of Final Work | 35 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | |
Supportive Courses | X |
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. | |||||
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. | |||||
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. | |||||
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 | 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 |