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研究生: 吳仁鈞
Ren jun Wu
論文名稱: 應用基因演算法於共同補貨週期之研究
Applying Genetic Algorithm to Common Replenishment Epochs
指導教授: 王福琨
Fu-Kwun Wang
口試委員: 陳欽雨
none
羅士哲
none
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業管理系
Department of Industrial Management
論文出版年: 2007
畢業學年度: 95
語文別: 中文
論文頁數: 81
中文關鍵詞: 共同補貨週期協調價格折扣基因演算法多產品缺貨
外文關鍵詞: Common replenishment epochs, Coordination, Price-discount, Genetic algorithm, Multiple products, Backorder
相關次數: 點閱:254下載:2
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  • 供應鏈管理中有一項非常重要的議題,即是如何發展出結合以及協調供應
    鏈之中各個成員的企業流程、決策與活動以改善整體供應鏈系統的績效和效率。
    在供應鏈中有多種不同類型的協調機制受到應用。透過價格折扣來進行供應鏈協
    調已經成為企業之間最受歡迎的方式之一。
    存在於供應鏈中的存貨可透過共同補貨週期機制來進行協調。共同補貨週期
    (Common Replenishment Epochs, CRE)是由Viswanathan and Piplani (V&P)所
    提出的一項協調機制,屬於二階供應鏈系統單一供應商補貨單一產品至下游數家
    買方的形式。在模式中,供應商為獲取節省訂單處理以及整合配送補貨的效益,
    可藉由價格折扣的方式用以吸引下游買方配合其預定補貨週期。然而,使用該協
    調機制會讓買方降低彈性以及提高存貨持有成本。因此供應商所提供的價格折
    扣,除了要能彌補買方因加入該協調模式所引發的額外成本外,還仍必須以所節
    省成本的利潤做為誘因,吸引買方加入進行協調。
    在本研究中我們應用基因演算法針對V&P 的模式進行修正並降低系統總成
    本。更進一步將單一產品的假設條件延伸成為多產品,經由數據分析後可以證實
    我們所提出的方法優於V&P 以及邱創鈞等人的方法。除此之外,在多產品模式
    中加入缺貨政策作為考量,驗證出在協調機制下供應商、買方以及系統總成本皆
    低於不允許缺貨發生時的成本。


    One of importance subject in supply chain management (SCM) is how to align
    and coordinate the business process, decisions and activities of the channel
    members to improve the overall performance and effectiveness. Various types of
    coordination mechanisms have been proposed in SCM. A common replenishment
    epochs (CRE) mechanism is a two-echelon supply chain system, in which a one
    vendor, multi-buyer supply chain for a single product has been proposed by
    Viswanathan and Piplani (V&P). In their model, a vendor can implement the CRE
    mechanism by offering price discount to all buyers. Under the proposed strategy, the
    buyers’ flexibility will be reduced and inventory costs will be increased. Therefore,
    the vendor offers price discount to compensate the buyer’s for any increase in
    inventory costs.
    In this research, we proposed a new method based on a genetic algorithm (GA)
    approach to revise V&P method and minimize the total system cost for multiple
    products. Using numerical experiments, we confirmed that our method outperforms
    V&P’s and Chiou et al.’s heuristics. In addition, we considered backorder policy in
    multi-product model. We proved that the total system cost by implementing CRE
    strategy with backorder policy is less than the cost without backorder policy.

    摘要................................................................I Abstract............................................................II 誌謝..............................................................III 目錄...............................................................IV 圖目錄..............................................................V 表目錄.............................................................VI 第一章 緒論.........................................................1 1.1 研究背景........................................................1 1.2 研究動機........................................................3 1.3 研究目的........................................................3 1.4 研究架構........................................................4 第二章 文獻探討.....................................................6 2.1 供應鏈協調模式(Supply Chain Coordination Models)................6 2.2 聯合訂購問題(Joint Replenishment Problem) ......................9 2.3 共同補貨週期(Common Replenishment Epochs)探討..................10 2.4 基因演算法(Genetic Algorithm)探討..............................13 第三章 模型建立....................................................19 3.2 允許缺貨下多產品共同補貨週期模式...............................29 3.3 比較協調後允許缺貨與不允許缺貨發生兩模式之差異.................33 3.4 基因演算法參數設定.............................................37 第四章 案例分析....................................................39 4.1 單一產品案例...................................................39 4.2 多產品案例.....................................................48 4.3 允許缺貨情況下多產品之案例.....................................60 第五章 研究結論與建議..............................................69 5.1 研究結論.......................................................69 5.2 研究貢獻.......................................................70 5.3 未來研究方向...................................................71 參考文獻...........................................................72

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