Operations Research II (IE323) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Operations Research II IE323 5. Semester 3 2 0 4 8
Pre-requisite Course(s)
IE222
Course Language English
Course Type Compulsory Departmental Courses
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. Barış YILDIZ
  • Research Assistant İrem BULANIK
Course Assistants
Course Objectives This course aims to ensure that students should have the ability to model and solve real-life problems using operations research techniques and be able to analyze results obtained with such models. Students are expected to understand the different types of models such as deterministic, stochastic, etc. and to be able to use computer programs to solve such models.
Course Learning Outcomes The students who succeeded in this course;
  • Will be able to demonstrate an understanding of the operations research modeling approaches and techniques.
  • Will be able to identify and formulate Integer Programming and Network problems; select and implement appropriate solution techniques.
  • Will be able to develop and solve Integer Programming models using appropriate software packages.
  • Will be able to demonstrate an understanding of the Project Management concept and techniques.
Course Content Modeling with integer variables; network models: model formulation, minimal spanning tree, shortest path, maximal flow problems, critical path method and program evaluation review techniques; nonlinear programming.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Integer Programming [1] pg. 475-476
2 Modeling Approaches in Mixed Integer Programming [1] pg. 477-511
3 Modeling Approaches in Mixed Integer Programming [1] pg. 477-511
4 Modeling Approaches in Mixed Integer Programming [1] pg. 477-511
5 Branch-and-Bound Algorithm [1] pg. 512-526
6 Branch-and-Bound Algorithm [1] pg. 512-526
7 Valid Inequalities and Gomory’s Cutting Plane Algorithm, Midterm I [1] pg. 545-561, [3] pg. 113-129
8 Assignment Problem [1] pg. 393-412
9 Travelling Salesman Problem [1] pg. 530-538
10 Minimum Spanning Tree Problem, Midterm II [1] pg. 456-458
11 Minimum-Cost Network Flow Problem [1] pg. 431-449, [2] pg. 453-481
12 Shortest Path Problem [1] pg. 414-418, [2] pg. 619-633
13 CPM Project Management [1] pg. 431-449
14 Maximum-Flow Problem [1] pg. 419-430, [2] pg. 607-619
15 Introduction to Nonlinear Programming [1] pg. 610-650
16 Final Exam

Sources

Course Book 1. Winston, W.L. Operations Research: Applications and Algorithms, 4th Edition, Duxbury Press, Belmont, California, USA.
Other Sources 2. Bazaraa, M.S., Jarvis, J.J., and Sherali, H.D., Linear Programming and Network Flows, 4th Edition, John Wiley & Sons, 2010.
3. Wolsey, L.A., Integer Programming, Wiley-Interscience, 1st Edition, 1998.
4. Hillier, F.S. and Lieberman, G.J., Introduction to Operations Research, 6th Edition, McGraw-Hill, 1995.
5. Taha, H. A., Operations Research: An Introduction, Prentice Hall, 1996.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics 7 15
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 50
Final Exam/Final Jury 1 35
Toplam 10 100
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 adequate knowledge in mathematics, science, and relevant engineering disciplines and acquires the ability to use theoretical and applied knowledge in these fields to solve complex engineering problems. X
2 Gains the ability to identify, formulate, and solve complex engineering problems and the ability 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 under realistic constraints and conditions to meet specific requirements and to apply modern design methods for this purpose.
4 Gains the ability to select and use modern techniques and tools necessary for the analysis and solution of complex engineering problems encountered in industrial engineering applications and the ability to use information technologies effectively. X
5 Gains the ability to design experiments, conduct experiments, collect data, analyze results, and interpret findings for investigating complex engineering problems or discipline specific research questions.
6 Gains the ability to work effectively in intra-disciplinary and multi-disciplinary teams and the ability to work individually.
7 Gains the ability to communicate effectively in written and oral form, acquires proficiency in at least one foreign language, the ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
8 Gains awareness of the need for lifelong learning and the ability to access information, follow developments in science and technology, and to continue to educate him/herself.
9 Gains knowledge about behaviour in accordance with ethical principles, professional and ethical responsibility and standards used in industrial engineering applications
10 Gains knowledge about business practices such as project management, risk management, and change management and develops awareness of entrepreneurship, innovation, and sustainable development. X
11 Gains knowledge about the global and social effects of industrial engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; 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. X
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 16 2 32
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics 7 1 7
Prepration of Midterm Exams/Midterm Jury 2 11 22
Prepration of Final Exams/Final Jury 1 27 27
Total Workload 200