查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

114-2 356914 最佳化理論 1 3.0 3 ★ 胡念祖自動化所
機電博所
機電外國學生專班 0 0 自動化所和機電博含外生班合開

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
114-2	356914	最佳化理論	1	3.0	3	★	胡念祖	自動化所機電博所機電外國學生專班	0	0	自動化所和機電博含外生班合開

教學大綱與進度：

教師姓名胡念祖　教師諮商時間(Office Hours)

Email nthu@ntut.edu.tw

最後更新時間 2025-12-17 20:57:48

課程大綱本課程將會介紹「非限制最佳化問題、線性規劃、非線性限制最佳化問題」。這些問題將會由數學推導與MATLAB模擬得到解決。對於解決非限制最佳化問題，一維搜尋法、梯度法、牛頓共軛方向法、擬牛頓法會將在本課程介紹及使用；線性規劃問題會利用單形法來解決；拉格朗日及KKT乘數則用來解決非線性限制最佳化問題。 Course Description：In this course, unconstrained optimization problems, linear programming, and nonlinear constrained optimization problems are presented. Mathematical derivations and MATLAB simulations are used to analyze and obtain the solutions to these problems. For unconstrained optimization problems, one-dimensional search, gradient, Newton's, conjugate direction, quasi-Newton methods are presented. For linear programming problems, simplex method is introduced. Last, Lagrange and Karush-Kuhn-Tucker multipliers are presented for solving nonlinear constrained optimization problems.

課程進度 1. 02/26 INTRODUCTION 2. 03/05 MATHEMATICAL REVIEW 3. 03/12 UNCONSTRAINED OPTIMIZATION- Basics of Set-Constrained and Unconstrained Optimization 4. 03/19 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 5. 03/26 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 6. 04/02 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 7. 04/09 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 8. 04/16 UNCONSTRAINED OPTIMIZATION-Gradient Methods 9. 04/23 Midterm Exam 10. 04/30 UNCONSTRAINED OPTIMIZATION-Gradient Methods 11. 05/07 UNCONSTRAINED OPTIMIZATION-Newton's Method 12. 05/14 UNCONSTRAINED OPTIMIZATION-Newton's Method 13. 05/21 UNCONSTRAINED OPTIMIZATION-Conjugate Direction Methods 14. 05/28 UNCONSTRAINED OPTIMIZATION-Conjugate Direction Methods 15. 06/04 LINEAR PROGRAMMING 16. 06/11 LINEAR PROGRAMMING 17. 06/18 Paper Presentation 18. 06/25 Paper Presentation PS: The contents will be adjusted according to actual needs

評量方式與標準 - Class participation: 15% - Assignments: 30% (No assignment turned in late will be accepted) - Midterm exam: 25% - Paper Presentation: 30%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：是
1. An Introduction to Optimization, 4th Edition, Edwin K. P. Chong, Stanislaw H. Zak, WILEY, 2013. 2. Optimization Concepts and Applications in Engineering (3rd ed.). Belegundu, A., & Chandrupatla, T., Cambridge: Cambridge University Press. 2019.

課程諮詢管道 TEL: (02)27712171 Ext. 4324
Email: nthu@ntut.edu.tw
Office Hours:
Wednesday 10:00-17:00
Integrate Technology Complex, Room 604-1

課程對應SDGs指標 SDG4：優質教育（Quality Education）
SDG17：夥伴關係（Partnerships for the Goals）

課程是否導入AI ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）

備註
Remote Learning will be performed via Microsoft Teams, if required (see https://news.ntut.edu.tw/p/422-1000-1085.php?Lang=zh-tw).

教師姓名	胡念祖　教師諮商時間(Office Hours)
Email	nthu@ntut.edu.tw
最後更新時間	2025-12-17 20:57:48
課程大綱	本課程將會介紹「非限制最佳化問題、線性規劃、非線性限制最佳化問題」。這些問題將會由數學推導與MATLAB模擬得到解決。對於解決非限制最佳化問題，一維搜尋法、梯度法、牛頓共軛方向法、擬牛頓法會將在本課程介紹及使用；線性規劃問題會利用單形法來解決；拉格朗日及KKT乘數則用來解決非線性限制最佳化問題。 Course Description：In this course, unconstrained optimization problems, linear programming, and nonlinear constrained optimization problems are presented. Mathematical derivations and MATLAB simulations are used to analyze and obtain the solutions to these problems. For unconstrained optimization problems, one-dimensional search, gradient, Newton's, conjugate direction, quasi-Newton methods are presented. For linear programming problems, simplex method is introduced. Last, Lagrange and Karush-Kuhn-Tucker multipliers are presented for solving nonlinear constrained optimization problems.
課程進度	1. 02/26 INTRODUCTION 2. 03/05 MATHEMATICAL REVIEW 3. 03/12 UNCONSTRAINED OPTIMIZATION- Basics of Set-Constrained and Unconstrained Optimization 4. 03/19 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 5. 03/26 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 6. 04/02 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 7. 04/09 UNCONSTRAINED OPTIMIZATION-One-Dimensional Search Methods 8. 04/16 UNCONSTRAINED OPTIMIZATION-Gradient Methods 9. 04/23 Midterm Exam 10. 04/30 UNCONSTRAINED OPTIMIZATION-Gradient Methods 11. 05/07 UNCONSTRAINED OPTIMIZATION-Newton's Method 12. 05/14 UNCONSTRAINED OPTIMIZATION-Newton's Method 13. 05/21 UNCONSTRAINED OPTIMIZATION-Conjugate Direction Methods 14. 05/28 UNCONSTRAINED OPTIMIZATION-Conjugate Direction Methods 15. 06/04 LINEAR PROGRAMMING 16. 06/11 LINEAR PROGRAMMING 17. 06/18 Paper Presentation 18. 06/25 Paper Presentation PS: The contents will be adjusted according to actual needs
評量方式與標準	- Class participation: 15% - Assignments: 30% (No assignment turned in late will be accepted) - Midterm exam: 25% - Paper Presentation: 30%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：是 1. An Introduction to Optimization, 4th Edition, Edwin K. P. Chong, Stanislaw H. Zak, WILEY, 2013. 2. Optimization Concepts and Applications in Engineering (3rd ed.). Belegundu, A., & Chandrupatla, T., Cambridge: Cambridge University Press. 2019.
課程諮詢管道	TEL: (02)27712171 Ext. 4324 Email: nthu@ntut.edu.tw Office Hours: Wednesday 10:00-17:00 Integrate Technology Complex, Room 604-1
課程對應SDGs指標	SDG4：優質教育（Quality Education） SDG17：夥伴關係（Partnerships for the Goals）
課程是否導入AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
備註	Remote Learning will be performed via Microsoft Teams, if required (see https://news.ntut.edu.tw/p/422-1000-1085.php?Lang=zh-tw).