ECTS - Special Topics in Operations Research

Atılım University - ECTS INFORMATION GUIDE

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 Question and Answer, Drill and Practice, Problem Solving.
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Danışment VURAL
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;
  • Formulate appropriate real-life problems using linear programming models.
  • Identify network (graph) problems in manufacturing or service systems and develop economical and effective solutions.
  • Gain proficiency in using computer-based software tools (e.g., GAMS) to solve various optimization problems.
Course Content Application of operations research techniques to a specified problem area.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction and Basic Concepts Overview of Operations Research Introduction to Network Optimization [Course Book] pp. 1–22
2 Graph Theory and Network Models Fundamental concepts in graph theory Directed and undirected graphs, network models [Course Book] pp. 23–52
3 Minimum Spanning Tree Overview of minimum spanning tree problems Kruskal's algorithm Prim's algorithm Sollin's algorithm Minimum Spanning Tree and Linear Programming [Course Book] pp. 510–542
4 Shortest Path Problems Overview of shortest path problems Bellman-Ford algorithm Dijkstra's algorithm Floyd-Warshall algorithm Shortest path problems and Linear Programming [Course Book] pp. 93–165
5 Transportation Problems Balanced transportation problems Unbalanced transportation problems Transportation Problems and Linear Programming [Bazaraa et al., 2011] pp. 513–535
6 Assignment Problems Definition of assignment problems Hungarian algorithm [Course Book] pp. 461–509
7 Midterm Exam
8 Travelling Salesman Problem (TSP) Definition of TSP Solution algorithms TSP and linear programming [Bazaraa et al., 2011] pp. 453–512 GAMS
9 Vehicle Routing Problems (VRP) Problem definition and notation Basic models and formulations [Toth & Vigo, 2014] pp. 1–28 GAMS
10 Araç rotalama problemleri (VRP) VRP türleri Çözüm yöntemleri ve yaklaşımlar [Toth & Vigo, 2014] s. 29–81 GAMS
11 Facility Location Problem definition and notation Basic models and formulations [Course Book] pp. 744–748 GAMS
12 Facility Location Continued exploration of variant models [Course Book] pp. 744–748 GAMS
13 Applications and Case Studies Real-world applications in logistics and transportation Case studies analysis GAMS
14 Applications and Case Studies Continued discussion on applications and case studies Course review and future research directions GAMS
15 Final Examination Period
16 Final Exam

Sources

Course Book 1. Ahuja, R. K., Magnanti, T. L., & Orlin, J. B. (1995). Network flows: theory, algorithms and applications. Prentice hall.
Other Sources 2. Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications. Society for industrial and applied mathematics.
3. Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D. (2011). Linear programming and network flows. John Wiley & Sons.
4. GAMS The General Algebraic Modeling Language

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics 1 10
Homework Assignments 1 10
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 45
Toplam 4 100
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 3 30
Presentation/Seminar Prepration
Project
Report
Homework Assignments 1 8 8
Quizzes/Studio Critics 1 8 8
Prepration of Midterm Exams/Midterm Jury 1 12 12
Prepration of Final Exams/Final Jury 1 19 19
Total Workload 125