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研究生： 謝垂燊
Chui-Shen Hsieh
論文名稱： 在直角多邊形上使用基因演算法畫樹之研究
指導教授： 何錦文
Chin-Wen Ho
高明達
Ming-Tat Ko
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
畢業學年度： 93
語文別： 中文
論文頁數： 66
相關次數： 點閱：11  下載：0 
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    • 論文提要及內容：
    一個圖形G(V, E)描述一個點集合V上的二元關係E，為一抽象的資料結構。圖形配置即是將圖形繪製在空間中，讓人們實際的觀察到此圖形的樣貌。而一個圖形配置的好壞取決於其可讀性，換句話說即能否把圖形所擁有的結構特性清晰地呈現出來。
    一般的繪圖演算法多為在無限制區域的二維或三維空間上產生圖形配置，但在某些情況下，我們會碰到只能在某個限定的不規則區塊上繪圖。例如想在VLSI既有的電路上加入新的電路。此時使用一般的繪圖演算法是無法處理的。
    在此論文，我們探討在給定二維空間上直角多邊形內繪製樹狀圖問題，提出一個以基因演算法為基礎的樹狀圖繪製演算法，並且結合階層式繪製的方式，將樹狀圖收縮後再逐層展開來做繪製。此演算法在處理300點以下的樹狀圖時已經有不錯的成效。

    目錄.........................................................................I 圖目錄.....................................................................III 表目錄.......................................................................V 第一章 緒論................................................................1 第二章 圖形繪製之相關研究..................................................6 2.1 在無限制配置空間上的演算法..............................................6 2.1.1 力導向演算法..........................................................7 2.1.1.1 彈簧嵌入演算法......................................................7 2.1.1.2 Kamada及Kawai的演算法...............................................8 2.1.2 模擬降溫演算法.........................................................9 2.1.3 基因演算法............................................................11 2.2 在限制配置空間上的演算法...............................................12 第三章 基因演算法之簡介...................................................15 第四章 繪圖演算法設計.....................................................20 4.1 階層式繪製.............................................................21 4.2 基因演算法之設計.......................................................24 4.2.1 物種的參數解編碼及初始化.............................................26 4.2.2 美學規則與適應值函數.................................................26 4.2.3 基因運算.............................................................32 4.2.4 終止條件.............................................................36 4.2.5 微調.................................................................36 4.3 族群基因演算法.........................................................36 第五章 結果與討論.........................................................39 5.1 參數值設定..............................................................39 5.2 結果與比較..............................................................48 第六章 結論與未來工作.....................................................60 參考文獻....................................................................64

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