Operations Research II (IE323) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Operations Research II IE323 3 2 0 4 8
Pre-requisite Course(s)
IE 222
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)
  • Assoc. Prof. Dr. Uğur BAÇ
  • Research Assistant İrem BULANIK ÖZDEMİR
Course Assistants
Course Objectives 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. Student should understand the different types of models, such as deterministic vs. stochastic. Students should be able to use software to solve such models.
Course Learning Outcomes The students who succeeded in this course;
  • Students will be able to demonstrate an understanding of the operations research modeling approaches and techniques.
  • Students will be able to identify and formulate Integer Programming and Network problems; select and implement appropriate solution techniques.
  • Students will be able to develop and solve Integer Programming models using appropriate software packages.
  • Students 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 A review of basic OR I and Introduction to Integer Programming [1] pg. 1-413 [1] pg. 475-476
2 Introduction to Integer Programming [1] pg. 475-476
3 Formulating (Mixed) Integer Programming Problems [1] pg. 477-511
4 Formulating (Mixed) Integer Programming Problems [1] pg. 477-511
5 Solving Integer Programming Problems-Relationship to Linear Programming-Branch and Bound [1] pg. 512-544
6 Solving Integer Programming Problems-Relationship to Linear Programming-Branch and Bound [1] pg. 512-544
7 Midterm I
8 Solving Integer Programming Problems-Implicit Enumeration-Cutting Plane Algorithm [1] pg. 545-561
9 Solving Integer Programming Problems-Implicit Enumeration-Cutting Plane Algorithm History of the Network Models, Terminology and Notation [1] pg. 545-561 [1] pg. 413-414
10 Midterm II Minimum Spanning Tree Problems-Prim’s algorithm, Kruskal’s algorithm [1] pg. 456-458
11 Minimum Spanning Tree Problems-Prim’s algorithm, Kruskal’s algorithm [1] pg. 456-458
12 Shortest Path Problems-Dijkstra’s algorithm [1] pg. 414-418
13 Maximum Flow Problems Ford-Fulkerson Algorithm, Max-flow Min-cut theorem [1] pg. 419-430
14 Maximum Flow Problems Ford-Fulkerson Algorithm, Max-flow Min-cut theorem Project Management, CPM and PERT, Crashing Project, Minimum Cost Network Flow Problems, Network Simplex [1] pg. 419-430 [1] pg. 431-449
15 Project Management, CPM and PERT, Crashing Project, Minimum Cost Network Flow Problems, Network Simplex [1] pg. 431-449
16 Project Management, CPM and PERT, Crashing Project, Minimum Cost Network Flow Problems, Network Simplex Introduction to Nonlinear Programming [1] pg. 431-449 [1] pg. 610-650

Sources

Course Book 1. Winston, W.L. Operations Research: Applications and Algorithms, 4rd Edition, Duxbury Press, Belmont, California, USA.
Other Sources 2. Hillier, F.S. and Lieberman, G.J., Introduction to Operations Research, 6th Edition, McGraw-Hill, 1995.
3. Wolsey, L.A., Integer Programming, Wiley-Interscience, 1st Edition, 1998.
4. 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 5 20
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 40
Final Exam/Final Jury 1 40
Toplam 8 100
Percentage of Semester Work 60
Percentage of Final Work 40
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 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. X
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. X
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. X
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 16 2 32
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics 10 1 10
Prepration of Midterm Exams/Midterm Jury 2 10 20
Prepration of Final Exams/Final Jury 1 26 26
Total Workload 200