Mathematical Engineering Area
With the development of computers, it has become possible to manage a large amount of information in a short time. On the other hand, more advanced mathematical analysis methods are required to present problems, and provide solutions based on this information. In the Mathematical Engineering area, students learn various engineering tools (models) that are powerful weapons in the practice of “proposing scientific management methods”, which is the purpose of management science and engineering. They learn the basic theory of each model through class sessions, and become able to utilize it as “practical knowledge” through seminars.
| Course name | Course description | Target year |
|---|---|---|
| Seminar on Mathematical Engineering | The objective of this course is to establish basic knowledge about various engineering tools (models) learned in each class of the area of modelling by mathematical engineering as ‘useful’ knowledge through exercises and practice. | 2 – 4 |
| Mathematical Optimization | Several topics of mathematical programming (linear programming, nonlinear programming, graph theory, combinatorial optimization method) are picked up and representative algorithms and basic theories are outlined. | 2 – 4 |
| Applied Probability | Basics of the probability theory and overview of Markov chain will be explained. Explanation of probability space, random variables, probability distribution, conditional probability, expectation values, conditional expectation, joint probability distribution, convergence of random variables, law of large numbers, central limit theorem, and Markov chain is planned. | 2 – 4 |
| Mathematical Statistics | In this course, students will acquire a basic knowledge of mathematical statistics using multivariate data through applied methods and applications. | 2 – 4 |
| Discrete Mathematics | This course will give introductory/general lectures on discrete mathematics and combinatorics, which are the basis of modeling/analysis of various discrete systems and information processing technology in policy and planning sciences. | 2 – 4 |
| Mathematical Analysis | Building on first-year calculus and linear algebra, this course revisits the fundamental concepts previously studied and introduces their applications and more advanced topics. | 2 – 4 |