臺灣博碩士論文加值系統

在排程問題中，當操作人員在對產品進行生產加工時，隨著時間的增加重複處理類似工作而獲得經驗與技巧等能力時，工作進行的加工時間會因此縮短，將此現象稱為「學習效果(Learning Effect)」。
目前有關具學習效果的排程問題，大多著重在單機做討論，而實際生產環境中，排程多屬於多機線型流生產排程。因此本論文探討n個工作件在m台機器上迴流r次且具有經驗學習效果之排程問題，設定所有機台具有相同的學習效果，目標為最大完工時間最小化。
本論文對於小工作件數的問題，使用列舉法求得最佳排序作為近似解演算法之評估準則；對於大工作件數的問題則利用四個起始解演算法與模擬退火法結合來求得近似解。由模擬的結果發現，不論樣本數的大小，由JH+NEH演算法與模擬退火法結合之改善效果最佳。

第一章 緒論 6
第一節 研究背景與動機 6
第二節 研究方法 8
第三節 研究架構 9
第二章 文獻探討 11
第一節 排程定義與分類 11
第二節 學習效果 13
第三節 迴流式生產排程 16
第四節 模擬退火法SA 18
第三章 問題描述與解題方法 20
第一節 符號與問題描述 20
第二節 本文演算法與其求解步驟 26
一、強森演算法(Johnson’s algorithm)： 26
二、NEH演算法： 27
三、模擬退火法(Simulated Annealing, SA) 28
四、倆倆交換(Pairwise exchange) 30
五、本論文演算法程序 32
第四章 資料模擬與分析 34
第一節 資料模擬 34
第二節 模擬結果 35
一、小工作件數 35
二、大工作件數 49
第五章 結論與未來研究方向 62
第一節 結論 62
第二節 未來研究方向 64
參考文獻. 65

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