Operations Research I (IE222) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Operations Research I IE222 4. Semester 3 2 0 4 7.5
Pre-requisite Course(s)
Math 275
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. Uğur BAÇ
  • Research Assistant İrem BULANIK ÖZDEMİR
  • Research Assistant Şevval KILIÇOĞLU
Course Assistants
Course Objectives Students should have the ability to model and solve real-life problems using linear programming techniques and analyze results obtained with such models. Students should be able to use software to solve a variety of models.
Course Learning Outcomes The students who succeeded in this course;
  • Students will acquire knowledge sufficient to use the deterministic O.R techniques, primarily the linear programming.
  • Students will be able to develop an appropriate model from a verbal description of a problem.
  • Students will be able to choose an approximate solution technique and solve engineering problems.
  • Students will be able to interpret relevant information from a model and/or a solution and interpret it.
  • Students will be able to develop and solve Linear Programming models using appropriate software packages.
Course Content Historical development of operations research, modeling, graphical solution, Simplex and dual Simplex methods, duality and sensitivity analysis, transportation, assignment, and transshipment problem.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to OR [1] pg. 1-9
2 A review of basic linear algebra [1] pg. 10-48
3 Introduction to Linear Programming [1] pg. 49-126
4 Introduction to Linear Programming The Graphical method [1] pg. 49-126 [1] pg. 50-99
5 The Graphical method [1] pg. 50-99
6 The Simplex algorithm [1] pg. 126-189
7 The Simplex algorithm [1] pg. 126-189
8 The Simplex algorithm [1] pg. 126-189
9 Sensitivity analysis [1] pg. 202-294
10 Sensitivity analysis [1] pg. 202-294
11 Midterm
12 Duality [1] pg. 295-334
13 Duality Transportation problems [1] pg. 295-334 [1] pg. 360-392
14 Transportation problems. Assignment and transshipment problems [1] pg. 360-392 [1] pg. 393-412
15 Assignment and transshipment problems [1] pg. 393-412
16 Assignment and transshipment problems [1] pg. 393-412

Sources

Course Book 1. Winston, W.L., Operations Research: Applications and Algorithms, 4th Edition, Brooks/Cole-Thomson Learning, 2004.
Other Sources 2. Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research and Revised CD-ROM 8, McGraw-Hill Science, 2005.
3. WU, N. and COPPINS, R., Linear Programming and Extensions, Cambridge University Press, 1981.
4. Anderson D. R., Sweeney D. J., and Williams T. A., An Introduction to Management Science, 11th Edition, West, 2004.
5. Taha, H. A., Operations Research: An Introduction, 8th Edition, Prentice Hall, 2006.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics 5 30
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 40
Toplam 7 100
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 Acquires sufficient knowledge in mathematics, natural sciences, and related engineering disciplines; gains the ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. X
2 Gains the ability to identify, define, formulate, and solve complex engineering problems; acquires the skill 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 to meet specific requirements under realistic constraints and conditions, and applies modern design methods for this purpose.
4 Develops the skills to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in industrial engineering applications; gains the ability to effectively use information technologies. X
5 Gains the ability to design experiments, conduct experiments, collect data, analyze and interpret results for the investigation of complex engineering problems or discipline-specific research topics. X
6 Acquires the ability to work effectively in intra-disciplinary and multidisciplinary teams, as well as individual work skills.
7 Acquires effective oral and written communication skills in Turkish; at least one foreign language proficiency; gains the ability to write effective reports, understand written reports, prepare design and production reports, make effective presentations, and give and receive clear instructions.
8 Develops awareness of the necessity of lifelong learning; gains the ability to access information, follow developments in science and technology, and continuously renew oneself.
9 Acquires the consciousness of adhering to ethical principles, and gains professional and ethical responsibility awareness. Gains knowledge about the standards used in industrial engineering applications.
10 Gains knowledge about practices in the business life such as project management, risk management, and change management. Develops awareness about entrepreneurship and innovation. Gains knowledge about sustainable development.
11 Gains knowledge about the universal and social dimensions of the impacts of industrial engineering applications on health, environment, and safety, as well as the problems reflected in the engineering field of the era. Gains 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 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 1 12 12
Prepration of Final Exams/Final Jury 1 22 22
Total Workload 188