成功大學數位學習平臺 V1(舊學期課程)

課程大綱(Course Outline)
英授(Taught in English)

Instructor:                        Kuangyou Bruce Cheng  (鄭匡佑), Associate Professor

E-mail/Phone: kybcheng@mail.ncku.edu.tw      (06)2757575-50361

Participators:  Graduate students and 4^th year undergrad students

Class Time:     09:10~12:00 Tuesday   

Office Hour:    09:00~12:00 Friday or by appointment

Language:                         English

 

Description:
The purpose of this course is to give students basic knowledge of numerical optimization algorithms and computational experience using these algorithms in programming. The basic concepts, minimization of one-variable and multivariable unstrained functions, techniques for the solution of multivariable constrained optimization problems, linear and quadratic programming techniques, and some global optimization methods are covered. Applications to different areas are also learned through completing term projects.

Prerequisites:

Calculus, General Physics, Matlab or C programming language

Syllabus:

1. Introduction; history of algorithm development
2. Convex and concave functions; statement of optimization problem; different classification
3. Single-variable optimization (with and without constraints)
4. Multi-variable optimization (with and without constraints)
5. Linear programming
6. Non-linear programming using function evaluation only
7. Conjugate directions; downhill simplex method
8. Non-linear programming using derivative information
9. Midterm exam
10. Project topic selection; Direct methods for constrained problems
11. Indirect methods for constrained problems
12. Dynamic optimization; Examples in biomechanics
13. Project midterm report due
14. Combinatorial optimization and integer programming
15. Genetic algorithm, simulated annealing, particle swarm method
16. Project presentation 1
17. Project presentation 2
18. Project report due

Textbook:No single textbook. Class notes will serve as our textbook.

Reference books:

1. Practical Mathematical Optimization (by Jan A. Snyman); with e-book at NCKU library

2. Engineering Optimization: Theory and Practice (4^th Edition, by Singiresu S. Rao)

3. Numerical Recipes in C, chapter 10.

 

Grading:

Homework:       40% (Late homework is not accepted. Your worst score will not be counted.)

Midterm exam:  30%

Project:            30% (3-4 people in a group; Presentation in English: 20%, Report:  10%)