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研究生:吳佩珊
研究生(外文):Pei-Shan Wu
論文名稱:應用改良式模糊約略集合與基因演算法於供應商評選
論文名稱(外文):Apply Adaptive Fuzzy Rough Set and Genetic Algorithm into the Supplier Selection
指導教授:梁文耀梁文耀引用關係
學位類別:碩士
校院名稱:國立彰化師範大學
系所名稱:資訊管理學系所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:127
中文關鍵詞:供應商管理供應商評選改良式模糊約略集合理論基因演算法
外文關鍵詞:Supply Chain ManagementSupplier SelectionAdaptive Fuzzy Rough SetGenetic Algorithms
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有效的供應鏈管理可有效因應顧客需求,降低企業生產成本並提升企業競爭力。其中,供應商的選擇與組成,主宰了整個供應鏈管理的成效。由於選擇正確的供應商為企業成敗的一個關鍵決策,如何透過各式各樣的評選準則去選擇出優良的供應商正是供應鏈管理文獻上廣泛討論的課題。然在供應商評選的文獻中,目前大多著墨於整體供應鏈的供應商評選為主,針對個別企業對零組件有需求的情況下而進行之零組件供應商評選的議題討論較少。本研究回顧供應鏈管理、供應商評選、約略集合理論與模糊理論的重要文獻,提出在滿足企業對零組件供應商之需求下,找尋整體產品之最適供應鏈之供應商評選方法。同時針對以往學者所提出之模糊約略集合演算法可能發生之缺失,調整修正而發展出「改良式模糊約略集合演算法」以作為零組件供應商篩選之規則產生方法。同時將前述產生之規則透過基因演算法之運算,正確且快速地求得在滿足企業需求之零組件供應商中所建立之最適產品供應鏈。整體而言,本研究發展出一套供應商評選之雛形系統,佐以實驗來驗證此改良式模糊約略集合演算法的成效。實驗結果顯示,經此改良式模糊約略集合演算法篩選過後之零組件供應商群中所產出整體產品最適供應鏈之總效用,明顯優於傳統使用人工所設定評選準則的門檻值以進行零組件供應商篩選與產出整體產品供應鏈之總效用。因此本研究所發展之供應商評選方法,不但為相關零組件供應商評選研究上提供了一套雛形系統,未來更可繼續發展成實用模型,協助企業在供應鏈管理實務上之決策。
Effective Supply Chain Management (SCM) can respond with the customers’ instant demand, lower the production cost, and enhance the competitive strength of the enterprise. Thus, how to evaluate and select the appropriate suppliers into the supply chain plays a critical role that determines the success or not of SCM. A plenty of research about the supplier selection had been conducted; however, most of them put attention on the supplier selection issues on the scope of whole supply chain system. Few researches have focused on how an individual company selects the component providers. After reviewing the literatures about the SCM, Supplier Selection, Rough Set Theory, and Fuzzy Theory, this study firstly developed the “Adaptive Fuzzy Rough Set” algorithm to generate the criteria for selecting the suppliers. Those criteria then were introduced into the Genetic Algorithms for generating the optimal supply chain. This supplier selection developed in this study was also empirically verified. The results point out that the generalized utility from the providers selected by this framework is significantly superior to those by traditional models in which the thres holds was manually and arbitrarily set. To sum up, this study not only provides a useful method in selecting the component providers for the SCM academic studies, but also helps to develop the practical module for the enterprise in deciding their component providers.
摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1.1 研究動機與背景 1
1.2 研究目的 4
1.3 論文架構 6
1.4 研究限制與範圍 7
1.5 研究流程架構 9
第二章 文獻探討 10
2.1 供應鏈管理 10
2.2 供應商評選 13
2.3 約略集合 19
2.4 模糊理論 24
第三章 研究方法 31
3.1 模糊約略集合演算法分析 32
3.2 供應商評選準則之選擇與評選方法 39
3.3 改良式模糊約略集合演算法 42
3.4 基因演算法 46
3.5 供應商評選方法 53
第四章 雛型系統與實驗分析 60
4.1 系統描述 60
4.2 基因演算法之參數說明 60
4.3 範例說明 62
4.4 實驗進行 95
第五章 結論與未來研究 108
參考文獻 110
附錄一 零組件供應商門檻值設定之問卷 117

圖目錄
圖 2-1 供應商評選流程 15
圖 2-2 上界近似與下界近似 21
圖 2-3 一般常用的標準隸屬函數 27
圖 2-4 三角型模糊數 28
圖 2-5 梯型模糊數 29
圖 3-1 改良式模糊約略集合演算法流程圖 44
圖 3-2 常見的基因編碼方式 47
圖 3-3 染色體交配方式(黑框為交配部分) 50
圖 3-4 染色體突變方法(黑框為突變部份) 51
圖 3-5 基因演算法流程圖 51
圖 3-6 供應商評選法流程圖 59
圖 4-1 範例流程圖 64
圖 4-2 隸屬函數 68
圖 4-3 基因演算法收斂圖 95
圖 4-4 實驗流程圖 97
圖 4-5 改良式模糊約略集合演算法之規則 102


表目錄
表2-1 Dickson 23 項供應商評選準則與Weber 之文獻整理 16
表2-2 供應商評選準則之文獻整理 18
表3-1 模糊約略集合演算法之相關研究 34
表3-2 傳統模糊約略集合演算法之優缺點 36
表3-3 模糊約略集合演算法之符號說明 38
表4-1 供應商部分資料表 60
表4-2 PC 基版之供應商資料表 66
表4-3 PC 基版之正規化供應商資料表 68
表4-4 PC 基版之模糊化供應商資料庫 69
表4-5 PC 基版之篩選過供應商資料庫 70
表4-6 LCD 觸控螢幕之供應商資料表 81
表4-7 LCD 觸控螢幕之正規化供應商資料表 82
表4-8 LCD 觸控螢幕模糊化供應商資料庫 83
表4-9 LCD 觸控螢幕之篩選過供應商資料庫 84
表4-10 基因演算法之部分初始母體 92
表4-11 第五代母體 93
表4-12 第20 代母體 94
表4-13 第40 代母體 94
表4-14 問卷整理之結果 99
表4-15 控制組之基因演算法結果 101
表4-16 實驗組之基因演算法結果 103
表4-17 控制組與實驗組總效用之結果 104
表4-18 T 檢定-獨立樣本檢定 106
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