教學大綱表 (112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.		 N4710
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
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 Applications Flow shop scheduling problems (FSSP) Using GA Flow Shop - encoding  
16 Applications Flow shop scheduling problems (FSSP) Using GA Flow Shop - encoding  
17 Final Report Final Report Final Report  
18 Final Report Final Report Final Report  
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：
教材編選(Teaching Materials)：
■ 1-1.簡報 Slids
■ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook Slids
□ 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：10%   報告：50%   彈性教學：10%   作業：30%  

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