臺灣博碩士論文加值系統

本研究探討供應多市場的製造商，面對不同需求曲線的多市場，且具有價格相依的不確定需求下，應如何以本身的有限產能和生產規模經濟等條件，進行多時點之採購、生產、運輸、庫存與供給等之營運規劃，以及定價策略，達到利潤最大之目標。本研究建構多階段與兩階段之動態營運規劃與定價策略之數學模式，並按模式特性以L型演算法(L-shaped)為架構，同時進行多階段與兩階段之動態營運規劃與定價策略之求解。
在數值分析中，本研究採用C公司之液晶電視供應鏈實際數據，進行多階段與兩階段之動態營運規劃與定價策略之求解，並進行生產成本之敏感度分析，以了解具有規模經濟之生產成本函數因係數改變而降低規模經濟顯著性後，對兩種隨機規劃之決策的影響。為理解兩種隨機規劃最佳解品質，本研究針對原數據和假設等各情境分別進行十六次抽樣，以求得各次抽樣之利潤和存缺貨成本的平均值，並分析各種重要績效指標對於利潤的影響。
研究結果發現，在本研究假設下，多階段隨機規劃確實可較兩階段隨機規劃擁有較好的績效表現。原因在於多階段隨機規劃可同時將多時點的需求不確定與資源條件納入考慮，將長期的產量集中在單一期間進行生產，再將產量做為庫存留待各期進行供給，妥善的在規模經濟所帶來之單位生產成本下降與存貨成本上升上作權衡；而兩階段隨機規劃由於只考慮近期內即將發生的需求不確定和規劃資源條件，而未考慮長期的資源條件與需求不確定變化，而未能將資源做有效的配置。

In this research, we primarily focus on decision-making for a manufacturer when consi-dering multi-period procurement, manufacturing, transportation, supply, inventory and pricing plan under uncertain demand, limited capacity and economic of scale in production in order to maximize manufacturer’s profit. The problem has been formulated as a two-stage and a multistage stochastic programming problem with the concept of dynamic pricing embedded to reflect manufacturer’s operational strategies.
The L-shapped method is empirically applied to solve the proposed two-stage and multis-tage stochastic programming formulations of Chi Mei Optoelectronics’s in-house LCD TV supply chain planning problem. In the numerical experiment, we generate 16 random problem instances with demand values sampled from realistic volumes to analyze the impact of critical factors on manufacturer’s revenue. In addition, a sensitive analysis has been performed to investigate the impact of economic of scale.
From the numerical results, we observe that a multistage formulation yields better system performance than a two-stage formulation due to the fact that the resource allocation can be adjusted in response to the uncertain demand realized in each stage.

目錄 I
表目錄 III
圖目錄 IV
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 研究範圍與限制 4
1.4 研究方法與流程 4
第二章 文獻回顧 7
2.1 供應鏈 7
2.1.1供應鏈的定義 7
2.1.2供應鏈管理 7
2.2 動態定價 (Dynamic pricing) 10
2.2.1 定義 10
2.2.2 動態定價之相關研究與文獻 10
2.3 隨機規劃 (Stochastic Programming) 16
2.3.1 不確定性(Uncertainty) 16
2.3.2 隨機規劃之定義 17
2.3.3 隨機規劃相關之研究與文獻 18
2.4 小結 23
第三章 供應鏈多階段隨機規劃時空網路建構 25
3.1 範圍與限制 25
3.2 時空網路之建構 28
3.2.1節點 28
3.2.2 節線 28
3.2.3 決策時點與時空網路 29

第四章 數學模式與求解步驟 33
4.1 參數與變數之符號 33
4.2 情境樹(Scenario Tree) 35
4.3需求不確定下動態定價之數學模式 38
4.3.1多階段隨機規劃模式 39
4.3.2兩階段隨機規劃模式 42
4.4 求解流程 43
4.5 價格切線通式推導 46
4.6 小結 51
第五章 數值分析 52
5.1 液晶電視產業簡介 52
5.1.1 液晶電視產品結構 52
5.1.2 液晶電視成本結構 53
5.1.3 液晶電視市場 54
5.1.4 液晶電視全球產業 55
5.2 問題規模與供應鏈結構 58
5.3 變數與參數設定 59
5.3.1 決策變數 59
5.3.2 參數 60
5.4 演算過程與數值分析 64
5.5 敏感度分析 71
5.6 小結 75
第六章 結論與建議 76
6.1結論 76
6.2 建議 79
參考文獻 82
一、中文部份 82
二、英文部分 82

一、中文部份
1.張益菁，「考量需求不確定之單階多廠產能規劃問題－以TFT LCD產業為例」，國立清華大學工業工程與工程管理研究所碩士論文，民國96年6月。
2.戴友椿，「需求不確定下動態定價模式之研究－以某筆記型電腦製造商為例」，國立成功大學交通管理科學系碩士論文，民國95年6月。
3.盛曉嵐，「實作應用於逆物流的EPC IS－以A公司LCD TV 供應鏈流程為例」，大同大學資訊經營研究所碩士論文，民國94年9月。
4.陳美妤，「TFT-LCD面板運輸模式之研究」，國立交通大學交通運輸研究所碩士論文，民國94年12月。
5.財團法人資訊工業策進會網站，http://www.iii.org.tw/。
6.奇美電子官方網站，http://www.benq.com.tw/benqstyle/。
7.明基官方網站，http://www.benq.com.tw/benqstyle/。
二、英文部分
1.Ahmed,S., King, A. J., Parija,G., A Multi-stage stochastic integer programming approach for capacity expansion under uncertainty, Journal of Global Optimization , Vol. 26, pp.3–24, 2003.
2.Al-Othman, W. B. E., Lababidi, H. M. S., Imad, M., Alatiqi, I. M., Khawla, A., Supply chain optimization of petroleum organization under uncertainty in mar-ket demands and prices, European Journal of Operational Research, Vol. 189 , pp.822–840, 2008.
3.Anupindi, R., Bassok, Y., Centralization of stocks : Retailors v.s manufacturer, Management Science, Vol. 45, No.2, pp. 178－191, 1999.
4.Chen, C. L., Lee, W. C., Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices, Computers and Chemical Engineering 28, pp. 1131–1144, 2004.
5.Christie, R. M. E., Wu, S. D., Semiconductor capacity planning: Stochastic modeling and computational studies, IIE Transactions 34, pp.131-143, 2002.
6.DisplaySearch, Quarterly global TV shipment and forecast report, Q4 2008.
7.DisplaySearch, Quarterly global TV shipment and forecast report, Q3 2008.
8.Gallego, G., Ryzin, G. V., Optimal dynamic pricing of inventories with stochas-tic demand over finite horizons, Management Science, Vol. 40, No. 8, pp. 999-1020, 1994.
9.Ganeshan, R., Harrison, T. P., An introduction to supply chain management, 1995.
10.Granot, D., Sosic, G., A three-stage model for a decentralized deistribution sys-tem of retailors, Operation Research, Vol.15, No.5, pp.771-784, 2003.
11.Gupta, A., Maranas, C. D., Managing demand uncertainty in supply chain plan-ning, Computers and Chemical Engineering 27, pp.1219-1227, 2003.
12.Hicks, M., When supply chain snaps, eWeek, 2002.
13.Khor, C. S., Elkamel, A., Ponnambalam, K., Douglas, P. L., Two-stage stochastic programming with xed recourse via scenario planning with economic and op-erational risk management for petroleum renery planning under uncertainty, Chemical Engineering and Processing,Vol.47, pp.1744–1764, 2008.
14.Li, Y. P., Huang, G. H., Nie, S. L., Liu, L., Inexact multistage stochastic integer programming for water resources management under uncertainty, Journal of Environmental Management, Vol. 88, pp.93–107 , 2008.
15.Liu, M. L., Sahinidis, N. V., Process planning in a fuzzy environment. European Journal of Operational Research, Vol. 100, Issue 1, pp.142-169, 1997.
16.MirHassani, S. A., Lucas, C., Mitra, G., Messina, E., Poojari, C. A., Computa-tional solution of capacity planning models under uncertainty, Parallel Compu-ting, Vol.26, pp. 511-538, 2000.
17.Netessine, S., Dynamic pricing of inventory/capacity with infrequent price changes, European Journal of Operational Research, Vol.174, pp.553-580, 2006.
18.Petkov, S. B., Maranas, C. D., Multiperiod planning and scheduling of multi- product batch plants under demand uncertainty, Industrial and Engineering Chemistry Research 36, pp.4864-4881, 1997.
19.Ray, D., Millman, S., Optimal inventory via customer service objectives, Inter-national Journal of Physical Distribution & Logistics Management, Vol.9, pp.325, 1979.
20.Santoso, T., Ahmed, S., Goetschalckx, M., Shapiro, A., A stochastic program-ming approach for supply chain network design under uncertainty , European Journal of Operational Research , Vol. 167, Issue 1, pp. 96-115, 2005.
21.Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E., Designing and managing the supply chain, 3rd edition, The McGraw Companies, Inc., New York, 2008.
22.Stock, J. R., Lambert, D. M., Strategic logistic management, 4 rd edition, The McGraw Companies, Inc., Boston, 2001.
23.Subrahmanyam, S., Pekny, J. F., Reklaitiso, G. V., Design of batch chemical plants under market uncertainty, Industrial & Engineering Chemistry Research, Vol.33, pp.2688-2701, 1994.
24.Shu,J., Teo,C.P., Shen,C.J.M., Stochastic transportation-inventory network de-sign problem, Operations Research, Vol. 53, No. 1, pp. 48–602005, 2005.
25.Tsiakis, P., Shah, N., Pantelides, C. C., Design of multi-echelon supply chain networks under demand uncertainty, Ind. Eng. Chem. Res. Vol.40, pp. 3585-3604, 2001.
26.Uribe, A. M., Cochran, J.K., Shunk, D. L., Two-stage simulation optimization for agile manufacturing capacity planning, Vol. 41, No. 6, pp.1181-1197, 2003.
27.Van Mieghem, J. A., Data, M., Price versus production postponement: Capacity and competition, Management Science, Vol. 45, No. 12, pp. 1631-1649, 1999.
28.Van Delft, C., Vial, J.P., A pratical implementation of stochastic programming: an application to the evaluation of option contracts un supply chain, Automation, Vol.40, pp. 743-756, 2004.
29.LCD downstream industry overview, Witsview LCD Research Institution, Q3 2008.
30.LCD downstream industry overview, Witsview LCD Research Institution, Q4 2008.
31.TFT-LCD panel price forecast, Witsview LCD Research Institution, Q4 2008.
32.TFT-LCD panel capacity status report, Witsview LCD Research Institution, Q3 2008.
33.Wurman, P. R., Dynamic pricing in the virtual market, IEEE Internet Computing, 2001.
34.Xu, X., Hopp, W. J., Dynamic pricing and inventory control with demand subs-titution：The value of pricing flexibility, Northwestern University, Department of Industrial Engineering, 2004.
35.You, P. S., Chen, T. C., Dynamic pricing of seasonal goods with spot and foward purchase demands, Computers and Mathematics with Applications, Vol. 54, Is-sue 4, pp. 490–498, 2007.
36.Zhao, W., Zheng, Y. S., Optimal dynamic pricing for perishable assets with nonhomogeneous demand, Management Science, Vol.46, No. 3, pp.375-388, 2000.