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 3 0 0 3 5
Pre-requisite Course(s)
N/A
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 Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Babek Erdebilli
Course Assistants
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
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 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.
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.
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.
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
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