Optimization Theory

Course Purpose
The purpose of this course is for students to obtain basic knowledge about optimization theory, especially, the dynamic programming method, the divide and conquer method, linear programming, and various basic optimization algorithms.
Learning Goals
Students will obtain basic knowledge of optimization theory and will acquire an understanding of how to use basic algorithms for solving various optimization problems.
Topic
Session 1Guidance, optimization problems and basic concepts of algorithms
Session 2Dynamic programming (1) (basic concept)
Session 3Dynamic programming (2) (design of basic algorithm)
Session 4Dynamic programming (3) (application to various optimization problems)
Session 5Dynamic programming (4) (application and practice to various optimization problems)
Session 6Split rule
Session 7Various discrete optimization problems and algorithms (1) (placement problems)
Session 8Various discrete optimization problems and algorithms (2) (network problems)
Session 9Various discrete optimization problems and algorithms (3) (machine learning)
Session 10Linear programming problem
Session 11Simplex method for linear programming problems (1) (basic algorithm)
Session 12Simplex method for linear programming problem (2) (algorithm in general case)
Session 13Dual theory, discrete optimization and continuous optimization
Session 14Advanced topics and summary
＊＊This content is based on April 1, 2024. For the latest syllabus information and details, please check the syllabus information inquiry page provided by the university.＊＊