Hiroshima University Syllabus

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Academic Year 2022Year School/Graduate School School of Informatics and Data Science
Lecture Code KA119001 Subject Classification Specialized Education
Subject Name システム最適化
Subject Name
Subject Name in
System Optimization
ムカイダニ ヒロアキ
Campus Higashi-Hiroshima Semester/Term 2nd-Year,  Second Semester,  3Term
Days, Periods, and Classrooms (3T) Mon9-10,Weds9-10:ENG 116
Lesson Style Lecture Lesson Style
(More Details)
Credits 2.0 Class Hours/Week   Language of Instruction B : Japanese/English
Course Level 2 : Undergraduate Low-Intermediate
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 01 : Mathematics/Statistics
Eligible Students
Keywords Optimization 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Criterion referenced
Informatics and Data Science Program
(Comprehensive Abilities)
・I2. Ability to provide the most appropriate system solution to a cross-sectional problem in the diversified and complicated information society based on the many forms of cutting edge information technology.
Class Objectives
/Class Outline
In this lecture, optimization is discussed to analyze mathematical sciences. By using these results, various operation which should be optimized is decided. 
Class Schedule lesson1 What is optimization?
lesson2 Unconstrained nonlinear optimization problem: multivariable calculus, gradient and Hessian matrix
lesson3 Unconstrained nonlinear optimization problem: application
lesson4 Constrained nonlinear optimization problem: Lagrange multipliers technique, examples
lesson5 Nonlinear optimization with inequality constraints (KKT condition)
lesson6 Numerical algorithm 1: contraction mapping
lesson7 Numerical algorithm 2: Newton's method
lesson8 Numerical algorithm 3: gradient descent method
lesson9 Variational calculus 1: Euler–Lagrange equation
lesson10 Variational calculus 2: various necessary conditions
lesson11 Variational calculus 3: Brachistochrone curve
lesson12 Variational calculus 4: geodesic
lesson13 Variational calculus 5: constrained case
lesson14 Optimal control problem
lesson15 dynamic programming: applications and examples 
Reference :田村明久,村松正和,「最適化法」,共立出版,ISBN4320016165
Reference :加藤直樹,「数理計画法」,コロナ社,ISBN9784339027198
Reference :太田光雄 編,「自動制御:電気・電子・情報基礎シリーズ3」,朝倉書店,ISBN9784254225938 
PC or AV used in
(More Details) blackboard 
Learning techniques to be incorporated  
Suggestions on
Preparation and
For each lecture, the review should be needed by reading the text book. Furthermore, the practical calculation and simulation would be helpful. 
Requirements Calculus and Linear Algebra are mandatory. 
Grading Method Mini-tests (10%) and Final exam (90%) 
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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