教學大綱 Syllabus

科目名稱:圖形理論

Course Name: Graph Theory

修別:選

Type of Credit: Elective

3.0

學分數

Credit(s)

30

預收人數

Number of Students

課程資料Course Details

課程簡介Course Description

Learn graph theory and its connection to computer science and networks.

核心能力分析圖 Core Competence Analysis Chart

能力項目說明


    課程目標與學習成效Course Objectives & Learning Outcomes

    1. Understand the basic idea of graph theory
    2. Understand basic algorithms of graph theory
    3. Can apply graph theory to related research

    每周課程進度與作業要求 Course Schedule & Requirements

    教學週次Course Week 彈性補充教學週次Flexible Supplemental Instruction Week 彈性補充教學類別Flexible Supplemental Instruction Type

    週次

    課程主題

    課程內容與指定閱讀

    教學活動
    與作業

    學習投入時數
    (課堂講授)

    學習投入時數
    (課堂前後)

    1

    Introduction 

    TBA

    TBA

    3

    2

    2

    No class (228)

    TBA

    TBA

    0

    0

    3

    Graphical Degree Sequence (I)

    TBA

    TBA

    3

    2

    4

    Graphical Degree Sequence (II)

    TBA

    TBA

    3

    2

    5

    Maximum Cardinality Matching (I)

    TBA

    TBA

    3

    2

    6

    Maximum Cardinality Matching (II)

    TBA

    TBA

    3

    2

    7

    Mathematical Programming and Primal Dual Transformation

    TBA

    HW1

    3

    2

    8

    Midterm exam I

    NA

    NA

    NA

    2

    9

    Maximum Weighted Matching (I)

    TBA

    TBA

    3

    2

    10

    Maximum Weighted Matching (II)

    TBA

    TBA

    3

    2

    11

    Stable Matching

    TBA

    TBA

    3

    2

    12

    Hamiltonian Cycle (I)

    TBA

    TBA

    3

    2

    13

    Hamiltonian Cycle (II)

    TBA

    TBA

    3

    2

    14

    Euler Tour

    TBA

    HW2

    3

    2

    15

    Midterm exam II

    NA

    NA

    NA

    2

    16

    Flexible Supplemental Instruction Week

    TBA

    TBA

    NA

    2

    17

    Flexible Supplemental Instruction Week

    TBA

    TBA

    NA

    2

    18

    Group Presentation

    NA

    NA

    3

    2

     

     

    授課方式Teaching Approach

    90%

    講述 Lecture

    10%

    討論 Discussion

    0%

    小組活動 Group activity

    0%

    數位學習 E-learning

    0%

    其他: Others:

    評量工具與策略、評分標準成效Evaluation Criteria

    Midterm: 25%*2
    Group presentation: 20%
    Homework: 10%*2
    Class Participation: 10%

    測驗藍圖
    問答題10題
    記憶: 10%
    理解: 40%
    應用: 10%
    獨立思考: 40%

     

    本課程完全開放使用生成式 AI 工具。

     

    指定/參考書目Textbook & References

    TBA

    已申請之圖書館指定參考書目 圖書館指定參考書查詢 |相關處理要點

    維護智慧財產權,務必使用正版書籍。 Respect Copyright.

    課程相關連結Course Related Links

    
                

    課程附件Course Attachments

    課程進行中,使用智慧型手機、平板等隨身設備 To Use Smart Devices During the Class

    需經教師同意始得使用 Approval

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