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題名：考慮產品結構樹於供應鏈網路流量管理之研究
作者：陳書儀
作者(外文)：Shu-Yi Chen
校院名稱：國立臺灣大學
系所名稱：資訊管理研究所
指導教授：陳靜枝
學位類別：博士
出版日期：2000
主題關鍵詞：供應鏈；供應鏈網路；供應鏈管理；網路流量演算法；產品結構樹；supply chain；supply chain network；supply chain management；network flow algorithm；product tree
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由於全球經濟體系的成形，企業無論大小都感受到來自全世界的競爭壓力。不僅如此，競爭壓力更進一步帶來對降低成本及快速反應的要求。正因如此，企業不僅必須加強本身的生產技術與成本控制，更必須在整個供應鏈網路（supply chain network）管理中創造更高的價值及新的市場機會，以期對環境作出更好的回應。然而，雖然許多研究都提出由整體觀點檢視供應鏈的重要性，也多半認為降低整體供應鏈的反應時間與成本，是面對市場的重要考量；但由於供應鏈管理希望能將所有牽涉產品生產、配銷過程的個體及其相互鏈結與影響均列入考慮，因此適用於單一地點的生產、存貨或物流管理模式，在整個供應鏈中未必能獲致最佳結果。此外，由於影響變數眾多，使得供應鏈管理的研究十分困難。因此，目前許多關於供應鏈的研究，都局限在觀念與方法的傳遞上，而較少見提出量化標準的探討；即使有數量化模型的建立，也大都較為複雜，雖然能適用於特定情況，卻不夠簡潔，也較不適於對整體供應鏈作簡明的描述與性質分析。
在上述的情況下，本研究希望提供一種較簡單且一般化的方式，使供應鏈網路能應用傳統網路流量中的演算法，來求解供應鏈網路中一些基本且重要的決策參數與生產路徑。因此本研究利用供應鏈網路與產品結構樹（product tree）之特性，將原始的供應鏈網路加以轉換，使得轉換後的供應鏈網路能直接應用最短路徑（shortest path）、最大流量（maximum flow）或最小成本流量（minimum cost flow）等演算法，並求解包括最低成本、網路內最低成本之生產路徑、最大流量及及生產路徑等重要的決策特性。因此，本研究之結果可以幫助實務界及學術界更瞭解供應鏈之特性及其應用。
簡言之，本研究希望採取新的方式來建立供應鏈網路之演算法模型，並建立四個不同演算法以求取最低成本及滿足此成本之生產子網路、最大流量及滿足此流量之子網路、滿足某需求量之最小成本子網路，已及以啟發式方法求解之滿足某需求量之最小成本子網路。由於本研究著眼與供應鏈整體的表現，因此能對供應鏈作更佳的描述及應用。舉例來說，利用本研究的成果，只要經過一些轉換過程，就能在一般的供應鏈網路中求出該供應鏈網路的最大生產量，以及可能的生產途徑。
隨著世界變化的速度提高，企業對供應鏈管理的需求也愈大。因此對供應鏈網路的研究與瞭解，將成為更重要的課題。本研究的成果能協助學術界及實務界持續認識供應鏈網路的性質，以建立更適配的生產決策，並進一步建立更好的人類生活。
The management of supply chains is getting more and more attention in a wired world demanding fast response and high flexibility with excellent service quality. There are, as there should be, many studies done to aid companies with better knowledge in operating their supply chains. However, these studies are either too conceptual to be directly put in use, or too specific and complex that fit only to their own conditions, and hence not easy to be applied to another case. Consequently, this research, instead of introducing concepts or building complicated models, intends to build quantitative supply chain models that are general enough for most supply chain cases.
In this study, the intended problems in supply chain management can be formulated as those found in network flow control models and can be solved by network flow algorithms. In other words, given the supply chain network and the product tree structure, the algorithms derived in the research transform the original supply chain network in a way that the transformed supply chain network can be used with some of the network flow algorithms. With the help of those classic network flow algorithms, such as shortest path algorithm, maximum flow algorithm and minimum cost flow algorithms, this research builds four algorithms that are applicable to most supply chain networks regarding the most important decision factors, namely cost and/or capacity allocation with only some transformation of the original supply chains. In this way, this study is valuable for both practitioners and academic researchers.
In conclusion, this research took a different approach to solve the integrated supply chain management problems. While focusing on the whole supply chain network, this research presents a new way to transform the supply chain network into a form that is good for evaluating some major decision variables. With the help of these algorithms, a supply chain manager can find either the maximum flow or the lowest cost sub-network in his supply chain and make the most use of the supply chain network. Moreover, the models are thus designed that with some modifications, they provide fast, feasible, and most of the time optimal solutions for any supply chains. As the world becomes more competitive and capricious, the supply chains also become more complex that it is impossible for a single company to handle. With the algorithms built in this study at hand, it will become easier for us to understand, control, and communicate the various properties of supply chains in different industries. Therefore more potential efficiency in supply chains will become possible for managers to extract, and this in turn will help businesses everywhere to better enhance human life.
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