N4710A 教學大綱表

教學大綱表 (113學年度第1學期)

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課程名稱 Course Title	(中文) 演化計算 (英文) Evolutionary Computation			開課單位 Departments	資訊經營學系
				課程代碼 Course No.	N4710A
授課教師 Instructor	康家榮
學分數 Credit	3.0	必/選修 core required/optional	選修	開課年級 Level	大四
先修科目或先備能力(Course Pre-requisites)：Python, Operations research
課程概述與目標(Course Overview and Goals)：Learn Simulated Annealing, Genetic Algorithm, Tabu Search, and Evolutionary Strategies, and Learn to Handle Constraints 1. understand why artificial intelligence is important 2. understand heuristics and meta-heuristics 3. understand particle swarm optimization 4. understand genetic algorithms 5. understand simulated annealing 課程概述與目標(Course Overview and Goals)： 1. 演化計算是重要的人工智慧技術，藉由模擬自然界的演化機制或模仿生物的智能行為，演化計算已用於解決參數優化、物流排程、機器學習、結構設計、機器人控制、甚至藝術創作…等許多複雜的最佳化問題。 2. 本課程介紹演化計算的基本概念、演算法設計、以及各項應用。 * 了解演化計算的概念與基礎。 * 認識演化計算的術語、運算子與演算法設計。 * 理解演化計算的理論。 * 學習如何將演化計算應用於最佳化及實際問題。 (此課程授課將同時使用中英文)
教科書(Textbook)
參考教材(Reference)

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
序 No.	單元主題 Unit topic	內容綱要 Content summary	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
1	Introduction	Course Introduction	Course Introduction
2	Basic Python Programming (1)	Python Programming Language	Python Programming Language
3	Basic Python Programming (2)	Python Programming Language	Python Programming Language
4	Basic Python Programming (3)	Python Programming Language	Python Programming Language
5	Combinatorial Optimization (1)	1. TSP、VRP 2. FSSP、JSSP 3. FLP	1. TSP、VRP 2. FSSP、JSSP 3. FLP
6	Combinatorial Optimization (2)	1. Guided Random Search Techniques (GRST) 2. Optimal solution 3. Bulls and Cows	1. Guided Random Search Techniques (GRST) 2. Optimal solution 3. Bulls and Cows
7	Genetic Algorithm (GA)	Genetic Algorithm (GA) – Basic (1)	1. Introduction 2. What is an Evolutionary Algorithm 3. Genetic Algorithm 4. Evolution Strategies 5. Genetic Programming
8	Genetic Algorithm (GA)	Genetic Algorithm (GA) – Basic (2)	6. Multi-Objective Evolutionary Algorithms 7. Working with Evolutionary Algorithms
9	Mid-Term Report	Mid-Term Report	Mid-Term Report
10	Discrete Coding	Coding for Discrete Decision Variables	Coding for Discrete Decision Variables
11	Permutation Coding	Coding for Permutation Solutions and Traveling Salesman	Coding for Permutation Solutions and Traveling Salesman
12	Applications	Vehicle Routing Problem (VRP) Using GA	VRP- encoding
13	Applications	Vehicle Routing Problem (VRP) Using GA	VRP- encoding
14	Applications	Job Shop Scheduling Problem (JSSP) Using GA	Job Shop - encoding
15	Final Report	Final Report	Final Report
16	Final Report	Final Report	Final Report
17	Final Report	Self-Directed Learning	Self-Directed Learning		彈性教學
18	Final Report	Self-Directed Learning	Self-Directed Learning		彈性教學

彈性教學週活動規劃

序 No.	實施期間 Period	實施方式 Content	教學說明 Teaching instructions	彈性教學評量方式 Evaluation	備註 Notes
1	起:2024-01-02 迄:2024-01-14	5.小專題 Project	Reading research articles	Written report

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：其他評量：20% 報告：60% 彈性教學：10% 作業：10%

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：https://curri.ttu.edu.tw/p/412-1033-1254.php