臺灣博碩士論文加值系統

建立供應鏈的核心競爭力是企業非常重視的議題，其中供應商評選則扮演著關鍵角色，合適的供應商將明顯地降低生產之成本與提升顧客服務水準。因此本文研究一個考量組裝次序規劃、生產線平衡與供應商風險之不確定性的供應商評選問題，並在評選準則中的運輸時間加入時窗限制，強調組裝中心如期生產的重要性，避免顧客的交貨日期延遲。為解決此供應商評選問題，本研究發展出一個穩健最佳化模式，來處理在多階供應鏈中具有供應商風險不確定性之供應商評選問題。此外，本研究也提出一種整合型基因演算法來求解穩健最佳化模式，為了驗證其求解之績效，本研究提出之演算法與另外兩個已知且目前較佳的演算法作案例實證有效性之比較。最後，提出穩健代價作分析，藉此可以探討保護程度與穩健代價之間的關係。另外，將穩健最佳化模式與確定性評選模式之結果作探究，提供決策者決定是否執行穩健規劃之必要性。

Establishing central competitiveness of supply chain is an issue strongly emphasized by enterprises. Among them, the supplier selection plays a key role. The suitable supplier will noticeably the reduce cost of production and promote Level of customer service. Therefore, this thesis studies the supplier selection problem with considering the assembly sequence planning, assembly line balancing problem, uncertainty of supplier risk, and also at transportation time of evaluation criterion to join time window constraints. The importance emphasized to assemble center to produce as scheduled, besides avoid delaying the customer''s date of delivery. This research develops a robust optimization mode, in order to solve the uncertainty of supplier risk of supplier selection problem in multi-stage supply chains. In addition, this text also puts forth the integration genetic algorithm to solve robust optimization mode. For identifying it solves of performance, these researches proposed of the algorithm have been already known with other two and better algorithm does the comparison of case substantial evidence usefulness currently. In the end, put forth the robust price analyzes. With this the study protective level and robust price both of relation. Besides, the result of robust optimization mode and determinism mode compares an investigation. Provide if the decision maker decision carries out the necessity of robust plan.

目 錄

摘 要 i
ABSTRACT ii
誌 謝 iv
目 錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 3
1.3 研究流程 4
第二章 文獻探討 7
2.1 供應商評選 7
2.2 組裝次序規劃 8
2.3 生產線平衡問題 10
2.4 時窗限制 12
2.5 多目標基因演算法 13
2.6 蟻群最佳化 15
2.7 穩健最佳化 16
2.7.1 Robust Optimization 17
2.7.2 Robust Counterpart Optimization 18
第三章 研究方法 20
3.1 問題描述與研究假設 20
3.2 研究架構 21
3.3 多目標最佳化數學模式 24
3.3.1 數學符號定義 24
3.3.2 多目標基本模式 26
3.3.3 穩健最佳化模式 31
3.4 整合式多目標演算法 33
3.4.1 蟻群系統動態非支配解基因演算法流程 34
第四章 實證案例與結果分析 47
4.1 案例描述 47
4.1.1 案例問題描述 47
4.1.2 實驗設計 53
4.1.3 案例結果 55
4.2 整合式多目標演算法績效評估 58
4.3 穩健規劃探討 62
第五章 結論與建議 66
參考文獻 68

表目錄

表2.1 穩健最佳化模式整理 19
表3.1 數學符號說明 24
表3.2 穩健數學符號說明 32
表4.1 頭戴式耳機之零件資訊表 48
表4.2 頭戴式耳機之結合關係資訊表 49
表4.3 頭戴式耳機之結合時間表 51
表4.4 頭戴式耳機之結合成本表 51
表4.5 各零件供應商資料表 52
表4.6 各參數組合NNS平均表 54
表4.7 各參數組合NPS平均表 54
表4.8 各參數組合ER平均表 55
表4.9 頭戴式耳機之最佳組裝次序規劃 55
表4.10 柏拉圖最佳解集合 56
表4.11 應商評選與零件採購結果 57
表4.12 各演算法執行績效之結果表 59
表4.13 保護程度Γ對目標函數的影響 62
表4.14 保護程度對穩健代價的影響 64

圖目錄

圖1.1 決策支援系統輔助示意圖 3
圖1.2 研究流程圖 6
圖2.1 組裝關聯圖 9
圖3.1 研究架構圖 23
圖3.2 蟻群系統動態非支配解基因演算法程序圖 35
圖3.3 染色體編碼示意圖 38
圖3.4 非支配解等級排序圖 39
圖3.5 排擠距離示意圖 40
圖3.6 排擠距離對分佈性的影響 41
圖3.7 輪盤法示意圖 43
圖3.8 供應商評選單點交配示意圖 43
圖3.9 生產線平衡單點交配示意圖 44
圖3.10 供應商評選雙點突變示意圖 44
圖3.11 生產線平衡雙點突變示意圖 45
圖3.12 菁英保留策略示意圖 45
圖4.1 頭戴式耳機之零件爆炸圖 48
圖4.2 頭戴式耳機之結合優先關係圖 49
圖4.3 頭戴式耳機之結合優先關係矩陣 50
圖4.4 最佳解之生產線平衡圖 57
圖4.5 各演算法之各目標比較分佈圖 61
圖4.6 保護程度對變異係數趨勢圖 64
圖4.7 保護程度對穩健代價趨勢圖 65

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