教學大綱表 (109學年度 第2學期)
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課程名稱
Course Title
(中文) 最佳設計分析
(英文) Optimun Design Analysis
開課單位
Departments
機械與材料工程研究所
課程代碼
Course No.
M5260
授課教師
Instructor
吳俊瑩
學分數
Credit
3.0 必/選修
core required/optional
選修 開課年級
Level
研究所
先修科目或先備能力(Course Pre-requisites):線性代數 微積分
課程概述與目標(Course Overview and Goals): 培養學生將工程問題化為數學模型選擇適當最佳化方法最後找出最佳設計的能力, 同時了解傳統方法(數學規劃法)與非傳統方法(演化式計算與仿生計算)的最佳化搜尋外, 對單目標, 多值域, 及多目標搜尋方法有基本了解及應用能力.
教科書(Textbook) J.S. Arora
Introduction to Optimum Design
2nd Ed., Elseiver Academic Press, 2004
參考教材(Reference) S.S.Rao
Engineering Optimizaton Theory and Practice
3rd Ed., John-Wiley & Sons, 1996
課程大綱 Syllabus 學生學習目標
Learning Objectives
單元學習活動
Learning Activities
學習成效評量
Evaluation
備註
Notes

No.
單元主題
Unit topic
內容綱要
Content summary
1 Introduction of optimization & applications 最佳化的目的, 問題及方法的歸類, 工程應用簡介 了解最佳化應用  
2 Basic mathematical concepts local and global minimma, gradient vector, Hessian matrix, Taylor's expansion, quadratic form, necessary and sufficient conditions 屬學基礎  
3 Single-variable minimization step size, search direction, bisection method, golden section method, polynomial approximation method 1D 搜尋  
4 Numerical method for unconstrained optimization search direction, step size
zero-order method, first-order method, and second-order method
多變數搜尋  
5 Introduction of constrained optimization problem necessary condition, sufficient condition, KKT conditions, Lagrange Multiplie 多變數限制條件搜尋  
6 constrained optimization problem KKT conditions, Lagrange Multiplier 多變數限制條件理論解  
7 Linear programming & simplex method standart LP definition, Basic concept of LP, 線性規劃基礎  
8 Linear programming & simplex method Simplex method, Two-phase simplex method 線性規劃數值方法  
9 期中考 考試 強化最佳化理論  
10 numerical method for constrained optimization problem basic concept, sequential LP, qadratic programming, constrained steepest descent 非線性限制條件問題  
11 numerical method for constrained optimization problem penalty function method & descent function 非線性最佳化  
12 Genetic Algorithm concept, algorithm, and applications of genetic algorithms 了解基因演算法的架構原理及應用  
13 Differential Evolution and Particle Swarm concpet, algorithm, applications of differential evolution and particle swarm 學習DE及PSO原理及應用  
14 Artificial Immune Algorithm concpet, algorithm, applications of artificial immune algorithm 學習類免疫演算法的原理,架構及應用  
15 multi-objective optimization concpet and applications of multi-objective algorithm 學習多目標最佳化的概念及應用  
16 engineering optimization optimization function of CAE programs
integration of commercial CAE programs with optimization programs
CAE軟體的最佳化功能
整合CAE軟體自動化設計及最佳化
 
17 Semester Project Report project report 應用最佳化於工程問題的專題報告  


教學要點概述:
1.自編教材 Handout by Instructor:
□ 1-1.簡報 Slids
□ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation: 期中考:30%   其他評量:10%   報告:40%   作業:20%  

教學資源(Teaching Resources):
□ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
扣考規定:http://eboard.ttu.edu.tw/ttuwebpost/showcontent-news.php?id=504