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研究生:洪宗意
研究生(外文):Tzung Yi Hung
論文名稱:應用限制解基因演算法於半導體製程分群問題
論文名稱(外文):Using the Limited-Solutions Genetic Algorithm to the Semiconductor Stages’ Clustering Problem
指導教授:李文義李文義引用關係
指導教授(外文):W.Y. Lee
學位類別:碩士
校院名稱:長庚大學
系所名稱:企業管理研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
論文頁數:79
中文關鍵詞:半導體製造群聚分析基因演算法
外文關鍵詞:Semiconductor ManufacturingCluster AnalysisGenetic Algorithm
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  • 下載下載:43
  • 收藏至我的研究室書目清單書目收藏:0
基因演算法的最大優點在於基因演算法是對染色體進行基因操作,而不是問題本身,不過一昧地追求數值上的最佳化而忽略了問題非數值的部分,導致基因演算法無法應用於某些問題。限制解基因演算法有別於一般的基因演算法的地方在於數值與非數值的結合,考慮到問題非數值的部分,並且有系統地找出數值部分的最佳解。
半導體製程是屬於連續型的製程,如果使用傳統的群聚分析或者是基因演算法來分組,將導致連續型的製程被切斷,所以本研究使用特殊的基因編碼方式,一開始就把解空間設定為連續型的資料分組,因為一開始就限定解空間,所以本研究的染色體交配與染色體突變也異於一般的基因演算法。
限制解基因演算法應用在半導體廠商的155道製程段分成25個製程群組的問題上,導入群聚分析在分群評量上的RMSSTD,使得限制解基因演算法可以應用於資料分群問題。並且利用特殊的基因編碼方式,引導基因演算法在限制的解空間中搜尋最佳解,找出半導體連續製程分組的最佳方式。
A Genetic Algorithm (GA) is a powerful search technique used in finding the optimal or near optimal solutions. However, focusing only on computation and ignoring the essence of the problems will cause disorientation in value domain. The Limited-solution Genetic Algorithm (LGA) is more advanced than classical Genetic Algorithm in analyzing value optimization and non-value problems in computing and finding appropriate solutions.
Semiconductor manufacturing process has a characteristic that a fixed operations sequence must be followed. If Cluster Analysis or a normal Genetic Algorithm is used in dividing data groups, the fixed operations sequence will be cut off. Therefore, in this study I set up a solution space as a continuous stage and input certain genetic codes to measure. This resulted in different Chromosome Crossover and Mutation than with normal Genetic Algorithm.
RMSSTD (Root-mean-square Standard Deviation) is added to the Limited-solution Genetic Algorithm which enables the algorithm to cluster the sequential operations in the same group. I constructed the genetic codes myself to find appropriate solutions, dividing the 155 operations into 25 groups. The solution is robust.
目錄
指導教授推薦書
口試委員會審定書
博碩士論文電子檔案上網授權書................................iii
長庚大學博碩士論文著作授權書................................iv
誌謝.....................................................v
中文摘要.................................................vi
英文摘要.................................................vii
目錄....................................................viii
圖目錄...................................................x
表目錄...................................................xi
第一章 緒論................................................1
第一節 研究背景與動機.......................................1
第二節 研究目的............................................3
第三節 研究架構............................................3
第四節 研究流程............................................5
第二章 文獻探討............................................6
第一節 半導體製程簡介.......................................6
第二節 群聚分析............................................10
2.2.1 個體間常用距離.......................................10
2.2.2 群與群之間的距離.....................................12
2.2.3 群集分析方法.........................................14
2.2.4分群評量指標..........................................16
第三節 基因演算法...........................................17
2.3.1 基因演算法簡介.......................................17
2.3.2 基因演算法操作簡介....................................19
第三章 限制解基因演算法.....................................23
第一節 限制解基因演算法與傳統基因演算法比較....................23
第二節 基因編碼............................................24
第三節 基因操作............................................26
3.3.1 染色體雜交...........................................26
3.3.2 染色體突變...........................................29
第四節 基因解碼............................................32
第五節 定義適應性函數.......................................33
第六節 隨機選取下一代.......................................35
第四章 應用限制解基因演算法於半導體製程整合最佳化...............36
第一節 數據標準化..........................................36
第二節 參數設定............................................36
第三節 結果................................................37
第四節 本章小結............................................48
第五章 結論與未來研究.......................................49
第一節 結論................................................49
第二節 未來研究............................................50
6.2.1 特徵值..............................................50
6.2.2 效率................................................50
參考文獻...................................................51
附錄一....................................................56
附錄二....................................................63

圖目錄
圖1.1 研究架構流程圖........................................5
圖2.1 基因演算法流程圖......................................19
圖3.1 基因演算法最佳解搜尋區域...............................23
圖4.1 遺傳五十代之適應性函數收斂圖...........................39
圖4.2 遺傳一百代之適應性函數收斂圖...........................41
圖4.3 遺傳兩百代之適應性函數收斂圖...........................43
圖4.4 遺傳五百代之適應性函數收斂圖...........................45
圖4.5 遺傳一千代之適應性函數收斂圖...........................47

表目錄
表3.1 基因池..............................................26
表3.2 分裂後的一號基因池....................................27
表3.3 分裂後的二號基因池....................................27
表3.4 排序後的一號基因池....................................27
表3.5 順序顛倒後的二號基因池.................................28
表3.6 排序後的二號基因池....................................28
表3.7 經過雜交之後新的染色體.................................28
表3.8 經過雜交以及突變之後新的染色體..........................31
表3.9半導體製程數據表.......................................34
表3.10 組內標準差對應表.....................................34
表4.1 參數設定表...........................................37
表4.2 遺傳五十代之最佳解....................................38
表4.3 遺傳一百代之最佳解....................................40
表4.4 遺傳兩百代之最佳解....................................42
表4.5 遺傳五百代之最佳解....................................44
表4.6 遺傳一千代之最佳解....................................46
林成梓,〈求取網格運算最大可靠度的資源配置演算法〉,國立交通大學,碩士論文,民國96年。

張敏勤,〈應用一個新的混合式基因演算法於分群問題〉,國立台灣科技大學,碩士論文,民國94年。

張巍贏,〈桁架結構最佳化設計使用基因演算法與窄化空間技術〉,國立交通大學,碩士論文,民國96年。

彭怡青,〈以統計測量為基礎之交易資料分群〉,國立台灣大學,碩士論文,民國90年。

廖京皇,〈應用改良型基因演算法於實測建築物之識別〉,朝楊科技大學,碩士論文,民國95年。

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