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)
N/A
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 Coordinator
Course Lecturer(s)
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 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 Ability to apply the acquired knowledge in mathematics, science and engineering
2 Ability to identify, formulate and solve complex engineering problems X
3 Ability to accomplish the integration of systems
4 Ability to design, develop, implement and improve complex systems, components, or processes
5 Ability to select/develop and use suitable modern engineering techniques and tools X
6 Ability to design/conduct experiments and collect/analyze/interpret data
7 Ability to function independently and in teams
8 Ability to make use of oral and written communication skills effectively
9 Ability to recognize the need for and engage in life-long learning
10 Ability to understand and exercise professional and ethical responsibility
11 Ability to understand the impact of engineering solutions
12 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