臺灣博碩士論文加值系統

在存貨管理問題中，供應鏈成員(例如零售商)都常利用經濟訂購量模式或最小最大政策來管理存貨。然而，由於等待貨品從上游供應商送達的可能需要相當長的前置時間，導致大量的安全存貨來因應需求的不確定性。本研究提出存貨調節機制，地理位置相近的供應鏈成員會自動形成群組。群組內的成員可以互相轉運存貨，藉以將存貨水準調整至正常的範圍內。在存貨調節機制下，當本期需求量過低時，供應鏈成員可以將過剩的存貨轉運給同群組內的其它成員，因此可以節省存貨持有成本。另一方面，當本期需求量過高時，及時地從同群組其它成員補充到存貨可以增加銷售量並維持顧客的滿意度。
利用轉運進行存貨調節機制會產生額外的成本支出。對於存貨調節機制的賣方來說，主要的成本為作業成本。賣方可以藉由轉運降低存貨持有成本並賺取賣出商品的價差。對於存貨調節機制的買方而言，相關的成本包含了查詢成本、作業成本、轉運價差、及運輸成本。然而，買方可以藉由轉運增加額外的銷售而獲利。
本研究建立數量模式來找出最佳的轉運數量，並利用數值分析區分適合應用存貨調節機制的狀況。分析結果發現賣方如果將多的藉由轉運運送給買方是有利的話。此種狀況下，群組內可以採用存貨調節機制。
由於無法直接從數量模式得到封閉解，故改由搜尋的方法找最佳解。本研究根據需求分配特性的不同，提出單峰二分搜尋法與全域搜尋法二種不同的演算法來找最佳的轉運數量。另一方面也利用模擬的方式進行驗證。在基本經濟訂購量模式下設計16種不同的情境、在非一次送達經濟訂購量模式下設計32種情境、而在數量折扣經濟訂購量下設計32種情境。模擬的結果發現當需求不穩定時，採用存貨調節機制可以提高供應鏈成員的淨收益，同時也亦能提高群組的總收益。

More often than not, a member in a supply chain(e.g. a retailer) manages its inventory based on the traditional EOQ model, or the min-max inventory policy, with simple modifications. However, since the lead time could be long, a member usually has to keep high safety stocks for so many merchandise items to meet the high service level requested by the customers. This study suggests differently that the member nearby in the same echelon should form a cluster to encourage the transshipment of stocks, so as to adjust every member’s inventory to the regular target level. Under this mechanism, the members with excess inventory are able to sell these surplus stocks, due to lower-than-expected demand, to those in short supply in the same cluster, and hence to reduce the carrying costs from keeping the excess inventory. On the other hand, the members in the same cluster running out of stocks also benefit by the timely supplies, which normally come faster than those from their suppliers, to serve and keep their customers.
The transshipment itself incurs additional costs. For the members with excess stocks, called “sellers”, to provide, the major cost incurred is the operation cost for the transshipment operation. Yet sellers also benefit from clearing up excess inventory, and by doing this, it leads to a lower carrying cost. Moreover, they are able to earn margins from the difference between their own purchase and selling prices. For the members requesting the transshipment, called “buyers”,, the costs include the communication / query cost, operation cost, the price difference and the transportation cost. However, buyers benefit from the orders they would have lost without those supplies, and hence revenue is increased by the transshipment.
This study constructed a mathematic model to find the optimal transshipment quantity for both parties and present the quantitative analysis to clarify the proper use of the transshipment mechanism. Because the mathematic model is too complicated to obtain a close-form solution, two search algorithms, BSA and GSA, were proposed in this study to find the optimal transshipment quantity based on the shape of the demand density functions. As results, the search algorithms provided the same optimal solution as the one found by using simulation model in 16 scenarios with basic EOQ model, 32 scenarios with non-instantaneous EOQ model, and 32 scenarios with quantity discount EOQ model. The results show that it is reasonable to adopt a transshipment mechanism to increase a member’s own net profit when facing abrupt demand, and even to benefit the cluster as a whole.

謝詞 一
論文摘要 二
THESIS ABSTRACT 三
目錄 四
圖目錄 六
表目錄 七
第一章 緒論 1
第一節 研究動機 1
第二節 研究目的 4
第三節 研究範圍 6
第四節 研究架構 7
第二章 文獻探討 8
第一節 供應鏈與供應鏈管理之定義 8
第二節 供應鏈研究範疇與模式分類 9
第三節 存貨控制模式分類 10
2-3-1 經濟訂購量模式 11
2-3-2 其它存貨控制模型 12
第四節 轉運問題 13
第三章 問題描述與存貨調節機制模式建構 17
第一節 問題描述 18
3-1-1 供應鏈網路架構 18
3-1-2 轉運規則 20
第二節 假設條件 22
第三節 基本經濟訂購量模式下的存貨調節機制 23
3-3-1 存貨調節機制之參數與變數 25
3-3-2 存貨調節機制買方的收益模型 27
3-3-3 存貨調節機制賣方的收益模型 31
3-3-4 採用存貨調節機制的目標函式 32
第四節 非一次送達經濟訂購量模式下的存貨調節機制 33
第五節 數量折扣經濟訂購量模式下的存貨調節機制 35
第六節 結論 37
第四章 存貨調節機制演算法 38
第一節 年期望轉運淨收益函數的性質分析 39
4-1-1 買方年期望轉運淨收益大於零的必要條件 40
4-1-2 賣方年期望轉運淨收益大於零的必要條件 43
4-1-3 年期望轉運淨收益最佳解發生的位置 44
4-1-4 年期望轉運淨收益最佳解發生的搜尋區間 45
第二節 搜尋演算法 50
第三節 演算法複雜度分析 55
第四節 結論 56
第五章 存貨調節機制模式分析 57
第一節 情境設計 57
5-1-1 情境設計因子 57
5-1-2 基本經濟訂購量模式下之情境設計 60
5-1-3 非一次送達經濟訂購量模式下之情境設計 61
5-1-4 數量折扣經濟訂購量模式下之情境設計 63
5-1-5 參數與求解環境設定 66
第二節 模擬方法 66
5-2-1 存貨政策 66
5-2-2 隨機因子 68
第三節 情境分析(一) — 應用於基本經濟訂購量模式 69
第四節 情境分析(二) —應用於非一次送達經濟訂購量模式 76
第五節 模式分析(三) — 應用於數量折扣經濟訂購量模式 80
第六節 數值分析 84
5-6-1 單期需求量變異程度的影響 84
5-6-2 同群組內供應鏈成員數目的影響 86
5-6-3 單位轉運購貨成本的影響 88
5-6-4 生產率的影響 90
5-6-5 折扣率的影響 92
第七節 結論 94
第六章 結論 95
第一節 總論 95
第二節 未來研究方向 96
參考文獻 97
附錄A、情境分析之結果 100
附錄B、轉運淨收益的95%信賴區間 108

[1] 林峻毅，「封測業將領先半導體景氣反彈」，太平洋證券股份有限公司，民國94年。
[2] Archibald, T. W., S. A. E. Sassen, and L. C. Thomas, “An Optimal Policy for a Two Depot Inventory Problem with Stock Transfer”, Management Science, Vol. 43, No. 2, February 1997, pp. 173—183.
[3] Axsater, S., “A New Decision Rule for Lateral Transshipments in Inventory Systems”, Management Science, Vol. 49, No. 9, September 2003, pp.1168—1179.
[4]Banerjee, A., J. Burtion, and S. Banerjee, “A Simulation Study of Lateral Shipments in Single Supplier, Multiple Buyers Supply Chain Networks”, International Journal of Production Economics, Vol. 81-82, 2003, pp. 103—114.
[5]Bartezzaghi, E. and R. Verganti, “Managing Demand Uncertainty Through Order Overplanning”, International Journal of Production Economics, Vol. 40, 1995, pp. 107—120.
[6]Burton, J. and A. Banerjee, “Cost-parametric analysis of lateral transshipment policies in two-echelon supply chain”, International Journal of Production Economics, Vol. 93—94, 2005, pp. 169—178.
[7]Chen, S. Y., W. L. Yang, and C. C. Chern, 2004, “Transshipment Effects on Inventory Management for Retailer Clusters”, Proceedings of the 35th Annual Meeting of Decision Science Institute, Boston, USA, pp.6591—6596.
[8]Chong, E. K. P. and S. H. Żak, An Introduction to Optimization, Second Edition, John Wiley & Sons, Inc., 2001.
[9]Chopra, S. and P. Meindl, Supply Chain Management: Strategy, Planning, and Operations, Pearson Education International, 2004.
[10]Christopher, M. G., Logistics and Supply Chain Management: Strategies for Reducing Costs and Improving Services, Pitman Publishing, 1998.
[11]Das, C., “Supply and Redistribution Rules for Two-Location Inventory System: One-Period Analysis”, Management Science, Vol. 21, 1975, pp. 765—776.
[12]Dick, E. B. and A. G. De Kok, “Controlling a Divergent 2-Echelon Network with Transshipments Using the Consistent Appropriate Share Rationing Policy”, International Journal of Production Economics, Vol. 45, 1996, pp. 369—379.
[13]Grahovac, J. and A. Chakravarty, “Sharing and Lateral Transshipment of Inventory in a Supply Chain with Expensive, Low-Demand Items”, Management Science, Vol. 47, No. 4, April 2001, pp.579—594.
[14]Gross, D., “Centralized Inventory Control in Multilocation Supply Systems”, In Multistage Inventory Models and Techniques, H. E. Scarf, D. M. Gilford and M. W. Shelly (eds.)., Stanford University Press, Stanford, Calif, 1963
[15]Harris, F. W., “How Many Parts to Make at Once”, Factory, The Magazine of Management, Vol. 10, 1913, pp. 135—136, 152.
[16]Hill, F. S. and G. J. Lieberman, Introduction to Operations Research, McGraw-Hill, 2001.
[17]Hoadley, B. and D. P. Heyman, “A Two-Echelon Inventory Model with Purchases, Dispositions, Shipments, Returns and Transshipments”, Naval Research Logistics Quarterly, Vol. 24, 1977, pp. 1—19.
[18]Hugos, M. and C. Thomas, Supply Chain Management in the Retail Industry, John Wiley & Sons, Inc., 2006.
[19]Karmarkar, U. S. and N. R. Patel, “The One-period N-location Distribution Problem”, Naval Research Logistics Quarterly, Vol. 24, 1977, pp. 559—575.
[20]Krishnan, K. S. and V. Rao, “Inventory Control in N. Warehouses”, Journal of Industrial Engineering, Vol. 16, No. 3, 1965, pp.212—215.
[21]Lancioni, R. A., “New Developments in Supply Chain Management for the Millennium”, Industrial Marketing Management, Vol. 29, 2000, pp. 1—6
[22]Lambert, D. M. and M. C. Cooper, “Issues in Supply Chain Management”, Industrial Marketing Management, Vol. 29, 2000, pp. 65—83.
[23]Lambert, D. M., M. C. Cooper, and J. D. Pagh, “Supply Chain Management: Implementation Issue and Research Opportunities”, International Journal of Logistics Management, Vol. 9, No. 2, 1998, pp. 1—19.
[24]Lee, H. L., “A Multi-Echelon Inventory Model for Repairable Items with Emergency Lateral Transshipments”, Management Science, Vol. 33, 1987, pp. 1302—1316.
[25]Lee, H. L., C. S. Jeong and C. Moon, “Information Distortion in Supply Chain: The Bullwhip Effect”, Management Science, Vol. 43, No. 4, 1997, pp. 546—558.
[26]Manber, U., Introduction to Algorithms: a Creative Approach, Pearson Education, 2003.
[27]Min, H. and G. Zhou, “Supply Chain Modeling: Past, Present and Future”, Computer & Industrial Engineering, Vol. 43, 2002, pp. 231—249.
[28]Norrman, A. and U. Jansson, “Ericsson’s Proactive Supply Chain Risk Management Approach After a Serious Sub-Supplier Accident”, International Journal of Physical Distribution & Logistics Management, Vol. 34, No. 5, 2004, pp. 434—456.
[29]Rabinovich, E., “Consumer Direct Fulfillment Performance in Internet Retailing: Emergency Transshipment and Demand Dispersion”, Journal of Business Logistics, Vol. 26, No. 1, 2005, pp. 79—112.
[30]Robinson, L. W., “Optimal and Approximate Policies in Multiperiod, Multilocation Inventory Models with Transshipments”, Operation Research, Vol. 38, 1990, pp.278—295.
[31]Rudi, N., S. Kapur, and D. F. Pyke, “A Two-Location Inventory Model with Transshipment and Local Decision Making”, Management Science, Vol. 47, No.12, 2001, pp. 1668—1680.
[32]Russell, D. M. and J. P. Saldanha, “Five Tenets of Security-Aware Logistics and Supply Chain Operation”, Transportation Journal, Vol. 42, No. 4, 2003, pp. 44—54.
[33]Sarkis, J. and R. P. Sundarraj, “Managerial Issues in Locating A Spare-Parts Hub for Digital Equipment Corporation”, Production and Inventory Management Journal, Vol. 43, Third Quarter 2002, pp. 47—54
[34]Silver, E. A., D. F. Pyke, and R. Peterson, Inventory Management and Production Planning and Scheduling 3rd Ed., Wiley, 1998.
[35]Simchi-Levi, D., P. Kaminsky, and E. Simchi-Levi, Designing and Managing the Supply Chain, McGraw-Hill, 2000.
[36]Tagaras, G., “Effects of pooling on the optimization and service levels of two-location inventory systems”, IIE Transactions, Vol. 21, 1989, pp.250—257.
[37]Tagaras, G., M. A. Cohen, “Pooling in Two-Location Inventory Systems with Non-Negligible Replenishment Lead Times”, Management Science, Vol. 38, No. 8, 1992, pp. 1067—1083.
[38]Taylor III, B. W., Introduction to Management Science, Pearson Prentice Hall, 2004.
[39]Van der Vorst, J. G. A. J. and A. J. M. Beulens, “Identifying sources of uncertainty to generate supply chain redesign strategies”, International Journal of Physical Distribution & Logistics Management, Vol. 33, No. 1, 2002, pp. 409—430.