2025 (Current Year) Faculty Courses School of Engineering Undergraduate major in Industrial Engineering and Economics
Operations Research
- Academic unit or major
- Undergraduate major in Industrial Engineering and Economics
- Instructor(s)
- Akiyoshi Shioura
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- IEE.A206
- Number of credits
- 200
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Mar 19, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course studies properties and solution methods for fundamental optimization models, which include Linear Programming, Nonlinear Programming, Network Optimization and Combinatorial Optimization Problems.
The technology of operations research is useful to do decision making for various problems in management sciences. Knowledge and ability acquired through this course will help students to solve real optimization problems in the future.
Course description and aims
By the end of this course, students will be able to:
・Understand fundamental properties of linear programming and use the simplex method.
・Understand fundamental properties of nonlinear programming and use the steepest descent method and the Newton method.
・Understand fundamental properties of network programming problems and use its solution methods.
・Understand fundamental properties of integer programming problems and use the branch and bound method.
Keywords
Linear programming, Nonlinear programming, network optimization, Combinatorial optimization
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
In each lecture, lecture materials will be uploaded to T2SCHOLA so that students can read and understand the content.
Before the end of the class, exercises related to the contents of the day's class will be presented, and students are expected to solve them before the next class as a report.
Submission of the report is optional, but points will be added to the final grade depending on how well the report is completed.
A mid-term exam and a final exam will be given to check the level of understanding.
Course schedule/Objectives
Course schedule | Objectives | |
---|---|---|
Class 1 | intoroduction to operations research and lienar programming | Instructions will be given in each class. |
Class 2 | linear programming | Instructions will be given in each class. |
Class 3 | linear programming | Instructions will be given in each class. |
Class 4 | linear programming | Instructions will be given in each class. |
Class 5 | linear programming | Instructions will be given in each class. |
Class 6 | combinatorial optimization | Instructions will be given in each class. |
Class 7 | mid-term exam | Instructions will be given in each class. |
Class 8 | network optimization | Instructions will be given in each class. |
Class 9 | network optimization | Instructions will be given in each class. |
Class 10 | network optimization | Instructions will be given in each class. |
Class 11 | nonlinear optimization | Instructions will be given in each class. |
Class 12 | nonlinear optimization | Instructions will be given in each class. |
Class 13 | nonlinear optimization | Instructions will be given in each class. |
Class 14 | final exam | Instructions will be given in each class. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
None required
Reference books, course materials, etc.
Course materials will be uploaded on T2SCHOLA.
Evaluation methods and criteria
Students will be assessed on their understanding of linear programming, nonlinear programming, network optimization, and combinatorial optimization, and their ability to apply them to solve problems.
Students' course scores are based on midterm and final exams and reports.
Related courses
- IEE.A330 : Advanced Operations Research
- IEE.A331 : OR and Modeling
- IEE.A202 : Mathematics for Industrial Engineering and Economics
Prerequisites
As a general rule, we accept only students in the Department of Industrial Engineering and Economics.
Other
The lecture materials of the year 2022 are available at the following web page.
http://www.iee.e.titech.ac.jp/~shioura/teaching/orf22/index.html