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    題名: 運輸規模經濟對多階層配銷物流策略之影響;The Impact of Transportation Economies of Scale on the Logistics Decision in Multi-Echelon Distribution System
    作者: 沈國基
    貢獻者: 工業管理研究所
    關鍵詞: 管理科學
    日期: 2010-07-01
    上傳時間: 2010-06-10 17:32:28 (UTC+8)
    出版者: 行政院國家科學委員會
    摘要: 運輸在配銷上創造了空間的效益,然而如果無法獲得有效率的運輸方式,物的流通將不會進行;根據調查,運輸成本約佔物流成本三分之ㄧ至三分之二,因此運輸成本的降低對整體物流成本的降低有著非常重要的角色,其效率又會影響多層級配銷體系之設計與建構。運輸規模經濟既為企業界在考慮需求空間分佈下,如何達成需求又能降低物流成本的重要考量,當然扮演著不容忽視的角色。然而在多層級配銷系統設計與建構模型上,運輸的規模經濟卻常被忽視,此肇因於如何將運輸規模經濟現象提出一有意義的模型,並將其加在多階層配銷系統設計之整合性問題上具有非常高之挑戰性。本研究擬以連續性概似模型來處理運輸規模經濟之主要二現象,亦即合併運送所達成的數量折扣與運送距離增加費率增加率漸減之現象(Tapering rate)。一般學者在處理多階層配銷系統之物流決策問題時,主要藉由離散式模型進行,但離散式模型資料量與電腦計算時間會因模型愈趨近實務而大幅增加,如此將讓離散式模型在多階層配銷系統之物流決策問題的應用性降低,而連續性概似模型基於少量資料的需求與接近最佳解的特性則可以補救上述的缺失(Dasci and Verter, 2001),連續性概似模型搭配最佳化的方法的使用可以是一個強大的求解問題工具 (Langevin, 1996)。因此在本研究我們將著重如何利用連續性概似模型來模型化運輸的規模經濟之主要現象-合併運送所達成的數量折扣與運送距離增加費率增加率漸減之現象,建構包含設施成本、運輸成本和存貨成本之總系統成本數學模型,主要的問題決策包含區域性配銷中心的設廠位置、如何分派零售商給區域性配銷中心、區域性配銷中心如何針對其負責之零售商決定其運輸決策以及這些配銷中心的存貨補充策略等,其目標為最小化整個系統成本。連續性概似技術將被應用於建構模型的過程中,我們將搭配使用非線性規劃相關技術以發展求解的方法,本研究將會面臨的挑戰即為如何以連續性概似模型趨近各成本以及如何發展非線性最佳化技術來求解問題。本研究主要貢獻在於提出如何在多層配銷系統之決策模型中中考量運輸規模經濟之現象,並分析與探討其對相關物流決策之影響。透過數值分析,我們將探討系統參數對系統決策與行為的影響,完整的數值分析將被用以驗證模型結果之正確性與現象之吻合度。我們期望藉由分析的結果,能提供相關於運輸規模經濟對於多層次物流運輸系統總成本之影響與管理意涵,使管理者在進行決策及經營上能更加準確而周全。 Transportation creates the value of place in distribution, however the delivery of goods will not take place if an efficient transportation does not exist. Transportation cost accounts for 1/3 to 2/3 of logistics cost (Davis and Drumm, 2002), and therefore make it a good candidate for logistics cost reduction. Designing an efficient multi-echelon distribution system is then an important task in practice. Transportation economies of scale is one of phenomena which should not be ignored when a company tries to cut down its distribution cost. Even though transporation economies of scale is important, to incorporate it in a decision model is challenging. In this study, we propose to use continuous approximation scheme to define two phenomena of transportation economies of scale, shipment consolidation and the tapering rate. Tapering is a phenomenon that the transportation rate increases with the distance but at a decreasing rate. Discrete models are popular in academics while dealing with a multi-echelon distribution system, but data and computational requirements increase tremendously as models become more realistic. Also, data reliability and hence model accuracy decrease. Continuous approximation could be a remedy to these weaknesses due to lesser data requirements and closed or near-closed form solutions (Dasci and Verter, 2001). The use of continuous approximation models in conjunction with optimization method has been proved to be a powerful tool for problem solving (Langevin, 1996). Therefore in this study, we will utilize continuous approximation models to describe the quantity discount due to shipment consolidation and the rate tapering due to the shipment distance increase, and then incorporate them in the model for solving the the integrated problem with facility, transportation and inventory sub-problems being considered simultaneously. The key decisions are where to locate the regional distribution centers (RDCs), how to assign retail stores to RDCs and how much inventory to hold at the different locations such that the total network cost is minimized. The challenges will be how to use continuous approximation model to estimate each system cost and how to develop non-linear optimization approach to solve the problem. A major contribution of this work will be lying in developing a continuous approximation modeling for describing the phenomena of transportation economies of scale and exploiting its impact on logistics decision. A complete numerical analysis will be designed to validate the correctness of the model and evaluate the system performance. Through the analysis, we should be able to provide the managerial insights about how transportation economies of scale impacts the system design decision and policy. These insights will lift the level of accuracy of management decision. 研究期間 : 9808 ~ 9907
    關聯: 財團法人國家實驗研究院科技政策研究與資訊中心
    顯示於類別:[工業管理研究所 ] 研究計畫

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