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School of Engineering
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- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
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- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Industrial Engineering and Economics
- Instructor(s)
- Matsui Tomomi
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Tue3-4(S011) Fri3-4(S011)
- Group
- -
- Course number
- IEE.A330
- Credits
- 2
- Academic year
- 2016
- Offered quarter
- 1Q
- Syllabus updated
- 2016/4/27
- Lecture notes updated
- 2016/4/28
- Language used
- Japanese
- Access Index
-
Course description and aims
This course covers some mathematical methods in operations research. The topics include, transportation problems, routing problems, network design problems, AHP and DEA. We also review some statistical models including Markov chain, queueing theory, and models for choice behavior. We discuss some topics related to game thery, e.g., stable marriage, spatial interaction model, linear production game, and social choice theory.
The objective of this course is to let students learn basic methods in operations research.
Student learning outcomes
By completing this course, students will have the necessary tools to do the following:
(1) Understand fundamental properties of optimization models
(2) Understand fundamental properties of statistical models
(3) Understand fundamental properties of some models related to game theory
Keywords
optimization problem, statistical model, game theory
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
In each class we give a lecture in the first half and then assign some exercise problems in the last half.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | overview of the lecture | Details will be given in each lecture. |
| Class 2 | transportation problem | |
| Class 3 | routing problem | |
| Class 4 | network design problem | |
| Class 5 | matrix for pairwise comparison | |
| Class 6 | analytic hierarchy process | |
| Class 7 | data envelopment analysis | |
| Class 8 | Markov chain | |
| Class 9 | queueing theory | |
| Class 10 | choice behavior | |
| Class 11 | stable marriage model | |
| Class 12 | spatial interaction model | |
| Class 13 | ｌnear production game | |
| Class 14 | social choice theory | |
| Class 15 | summary of the lecture |
Textbook(s)
None
Reference books, course materials, etc.
M. Mori and T. Matsui, ``Operations Research,'' Asakura Publishing Co., Ltd., 2004.
Assessment criteria and methods
Midterm and final exams 70%, exercise problems 30%.
Related courses
- IEE.A206 ： Operations Research
- IEE.A430 ： Numerical Optimization
Prerequisites (i.e., required knowledge, skills, courses, etc.)
No prerequisites are necessary, but enrollment in related courses is desirable.
