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研究生:汪玉柏
研究生(外文):Yu-Po Wang
論文名稱:運用基因演算法求解流程型工廠之多目標排程
論文名稱(外文):An Application of Genetic Algorithm for Scheduling in Flowshop with Multiple Objectives
指導教授:廖慶榮廖慶榮引用關係
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:管理研究所工業管理學程
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:1999
畢業學年度:87
語文別:中文
論文頁數:67
中文關鍵詞:基因演算法流程型工廠排程多目標
相關次數:
  • 被引用被引用:30
  • 點閱點閱:548
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
過去的排程研究中大多只針對單一準則,可是在實務上,多準則的問題卻更能符合實務上的需要,所以近年來多準則排程問題的研究也有逐漸增加的趨勢。但是綜觀目前多準則的相關文獻,大多仍屬於雙準則或是單一機器的研究,針對多準則及多機的探討文獻還是相當缺乏,然而探討多機的排程問題又有其存在的必要性,因為單機的情形在實際作業上並不多見,故本研究擬以流程型工廠 (flow-shop) 之排程問題為主,並將使用最大完工時間、總流程時間以及機器閒置時間作為衡量準則。
由於基因演算法 (genetic algorithm) 在處理複雜問題上的效果備受肯定,因此,本研究將運用基因演算法作為主要的演算架構,進而針對流程型工廠多機多準則之排程問題,發展出一套合適的演算模式,並且提供給決策者較佳的有效排程 (efficient schedule) 集合。
最後,本研究也將與目前在同樣問題上的研究進行分析比較,以證明本研究的績效以及實際的應用價值。
關鍵詞:基因演算法、流程型工廠排程、多目標
第一章 導論1
1.1. 研究動機1
1.2. 研究範疇與目的3
1.2.1. 模式之假設條件3
1.2.2. 多目標決策的研究方向3
1.2.3. 有效排程4
1.2.4. 變動權重5
1.3. 研究方法與架構7
第二章 相關文獻探討9
2.1. 雙機問題9
2.2. 多機問題10
第三章 基因演算法12
3.1. 基本原理與起源12
3.2. 基因演算法執行流程12
3.3. 基因演算法的參數設定21
3.4. 基因演算法的應用22
第四章 研究方法24
4.1. 問題模式24
4.1.1. 符號說明24
4.1.2. 績效衡量準則25
4.2. 演算方法27
4.3. 演算流程27
4.4. 演算實例33
第五章 實驗結果與說明42
5.1. 參數設定42
5.2. 實驗結果與分析47
5.2.1. 與Rajendran的比較47
5.2.2. 與Sridhar和Rajendran的比較53
5.3. 綜合分析59
第六章 結論與未來研究方向61
6.1. 結論61
6.2. 未來研究方向62
參考文獻63
附錄 DELTA指標的計算方式66
作者簡介67
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