Hiroshima University Syllabus

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Academic Year 2022Year School/Graduate School School of Engineering
Lecture Code K5130010 Subject Classification Specialized Education
Subject Name 数理最適化
Subject Name
Subject Name in
Mathematical Optimization
キタムラ ミツル
Campus Higashi-Hiroshima Semester/Term 2nd-Year,  Second Semester,  4Term
Days, Periods, and Classrooms (4T) Thur5-8:ENG 115
Lesson Style Lecture Lesson Style
(More Details)
Face-to-face Lecture if possible 
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 3 : Undergraduate High-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 10 : Integrated Engineering
Eligible Students 2nd year students
Keywords Optimization 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Criterion referenced
Program of Mechanical Systems Engineering
(Abilities and Skills)
・Acquring basis of mechanical system engineering steadily and developing the applied skill.

Program of Transportation Systems
(Knowledge and Understanding)
・The area of systems: Technical knowledge on systems, information and transportation systems relating to transportation equipment and coexistence with the environment
(Abilities and Skills)
・The area of systems: The ability to apply technical knowledge of systems, information and transportation systems to solve issues relating to the areas of transportation equipment and coexistence with the environment 
Class Objectives
/Class Outline
Class Schedule lesson 1 Guidance and Linear Programing
lesson 2 Slack variables and Simplex method
lesson 3 Dual problem
lesson 4 Multi objective problem
lesson 5 Nonlinear optimization problem, Taylor expansion equation and Numerical derivatives
lesson 6 One variable search and Steepest descent method
lesson 7 Newton method
lesson 8  Quasi-Newton method
lesson 9 Quasi-Newton method,  Conjugate gradient method
lesson 10 Conjugate gradient method (step version), Successive linear programming (SLP)
lesson 11 Penalty function method, SUMT method
lesson 12 Lagrange multiplier method
lesson 13 Inequality constraint problem
lesson 14 Krush-Kuhn-Tucker condition (KKT condition)
lesson15 Genetic Algorithm

Finial examination is given 
PC or AV used in
(More Details) Textbook and PC.
Sometime Excel is used. 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Study hard 
Grading Method Examinations and homework 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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