生命週期需求模式下考量缺貨或折現的最佳訂購策略｜國立臺灣科技大學博碩士論文系統

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研究生：	翁慈君 Tzu-chun Weng
論文名稱：	生命週期需求模式下考量缺貨或折現的最佳訂購策略 Optimal replenishment policies for the product-life-cycle demand with shortages or discounting consideration
指導教授：	陳正綱 Cheng-kang Chen
口試委員:	葉瑞徽 Ruey-huei Yeh 洪大為 Ta-Wei Hung
學位類別：	碩士 Master
系所名稱：	管理學院 - 資訊管理系 Department of Information Management
論文出版年：	2005
畢業學年度：	93
語文別：	英文
論文頁數：	57
中文關鍵詞：	產品生命週期、Nelder-Mead algorithm 、折現率、缺貨、存貨補充
外文關鍵詞：	discounting, shortage, Nelder-Mead algorithm, product life cycle, inventory replenishment
相關次數：	點閱：472 下載：14
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上一筆

公司的管理者每年將依據市場的需求，做出有利於公司的決策，以訂購能符合最低的成本且滿足消費者需求的產品量。因為存貨的金額佔公司營運資金相當高的比例，所以如何協助企業訂定最佳存貨補充策略，做好存貨管理工作，就能間接增加公司的獲利能力。因此，相當多的學者致力於存貨模式的發展。
過去的學者在探討存貨模式時，不外乎探討線性需求或是曲線需求模式。然而，現實社會中，產品的需求有所謂的生命週期，產品生命週期大致可以劃分為四個主要的階段：市場進入階段、市場成長階段、市場成熟階段、銷售衰退階段。
因此本論文發展出一個較符合現實的產品需求模型，並分析其模型，並以Nelder-Mead algorithm解決我們的問題，求解出最佳的訂購時間及訂購量，以提供最佳的存貨策略且符合最低的營運成本，讓管理者有較佳的參考來做出較完善的決策方針。同時，我們將探討存貨成本與缺貨成本的關係或是考慮折現率的存在，對存貨模式造成變動後，將如何降低公司營運的成本。

Corporation managers make decisions which benefit corporation in accordance with demand of markets every year and order quantities of products which conform the lowest cost and satisfy the demand of consumers. Because inventory cost is a large proportion of the working capital for many companies, good inventory management by helping corporations to determine the optimal inventory replenishment policies increasing the ability of making profits indirectly. So many researchers were denoted to the development of inventory models.
Past researchers confer inventory models which are linear demand or curve demand. However demand of production has life cycle in fact. Product life cycle demarcate approximately four main phases: enter, growing, mature, and decayed. In this paper, we explore the demand function follows the product-life-cycle shape for the decision maker to determine the optimal number of inventory replenishments and the corresponding optimal inventory replenishment time points in the finite planning horizon. A complete search procedure is provided to find the optimal solution by employing the Nelder-Mead algorithm. Also, based on the search procedure developed in this paper, a decision support system is implemented on a personal computer to solve the proposed problem. Let managers have decision-making reference which is more than others to support better decision guiding principle. Simultaneously, we talk over the variation of the inventory model caused by holding cost and shortage cost or discounting conferred how to reduce the operating cost.

致  謝	I

摘  要	II
Abstract	III

TABLE OF CONTENTS	IV
LIST OF FIGURES	VI
LIST OF TABLES	VII

Chapter 1. Introduction	1
Investigate background and motive	1
1.2 Investigate objective	2
1.3 Investigate scope and restriction	3
1.4 Investigate method and procedure	4

Chapter 2. Literature review	5
2.1 A finite horizon model	6
2.2 A finite horizon model with shortages considered	9
2.3 A finite horizon model with discounting conferred	11

Chapter 3. Assumption and Notations without shortage	12
3.1 The assumptions about demand function	12
3.2 Other assumption of our model	14
3.3 Notations	15

Chapter 4. Mathematical Formulation of Our Model	16
4.1 The model based on EOQ	16
4.2 The model based on EOQ with shortages considered	18
4.3 The model based on EOQ with discounting conferred	20

Chapter 5. Solution Procedure	21
5.1 Review of the Nelder-Mead algorithm	22
5.2 Algorithmic structure for Nelder-Mead algorithm	25
5.3 Apply Nelder-Mead algorithm to solve our problem	27
5.3.1 Finding the optimal replenishment time points ti*	28
5.3.2 Finding the optimal number of replenishments n*	31
5.3.3 Combine two methods to solve our problem	33

Chapter 6. Computer Implementation	34

Chapter 7. Numerical Example and Sensitive Analysis	39
7.1 Mathematical procedure of Nelder-Mead algorithm	39
7.2 Numerical Example of model based on EOQ with shortages considered	43
7.3 Numerical Example of model based on EOQ with discounting conferred	47

Chapter 8. Concluding Remarks   52

Reference	  53

                                

Amrani, M., and Rand, G. K. (1990). An eclectic algorithm for inventory replenishment for items with increasing linear trend in demand. Engineering Costs and Production Economics, 19, 261-266.
Barbosa, L. C., & Friedman, M. (1978). Deterministic inventory lot size models – a general root law. Management Science, 24(8), 819-826.
Benkherouf, L. (1994). On the replenishment policy for an inventory model with linear trend in demand and shortages. Journal of the Operational Research Society, 45(1), 121-122.
Brosseau, L. J. A. (1982). An inventory replenishment policy for the case of a linear decreasing trend in demand. INFOR, 20(3), 252-257.
Buzacott, J. A. (1975). Economics order quantities with inflation. Operational Research Quarterly, 26, 553-558.
Casella, G.., & Berger, R. L. (1990), Statistical Inference. Pacific Grove, California: Brooks/Cole Publish.
Chandra, M. J., and Bahner, M. L. (1985). The effects of inflation and the time value of money on some inventory systems. International Journal of Production Economics, 23(4), 723-730.
Chung, K. J. and Lin, Chuan. N. (2001). Optimal inventory replenishment models for deteriorating items taking account of time discounting. Computers & Operations Research, 28, 67-83.
Dave, U. (1987). On (Ti, Si) policy inventory system with demand changing linearly increasing with time. Cahiers du CERO 29, 229-234.
Dave, U. (1989). A deterministic lot-size inventory model with shortages and a linear trend in demand. Naval Research Logistics, 36, 507-514.
Dave, U. (1989). On a heuristic inventory-replenishment rule for items with a linearly increasing demand incorporating shortages. Journal of Operational Research Society, 40(9), 827–830.
Datta, T. K., & Pal, A. K. (1992). A note on a replenishment policy for an inventory model with linear trend in demand and shortages. Journal of Operational Research Society, 43(12), 993–1001.
Deb, M., & Chaudhuri, K. (1987). A note on the heuristic for replenishment of trended inventories considering shortages. Journal of Operational Research Society, 38(5), 459–463.
Donaldson, W. A. (1977). Inventory replenishment policy for a linear trend in demand - an analytical solution. Operational Research Quarterly, 28(3), 663-670.
Goyal, S.K. (1988). A heuristic for replenishment of trended inventories considering shortages. Journal of Operational Research Society, 39(9), 885–887.
Goyal, S.K., Morin, D., & Nebebe, F. (1992). The finite horizon trended inventory replenishment problem with shortages. Journal of the Operational Research Society, 43(12), 1173-1178.
Goyal, S. K. (1994). Determining economic replenishment intervals for linear trend in demand. International Journal of Production Economics, 34, 115-117.
Goyal, S.K., Hariga, M.A., & Alyan, A. (1996). The trended inventory lot sizing problem with shortages under a new replenishment policy. Journal of the Operational Research Society, 47(10), 1286-1295.
Goyal, S. K., and Giri, B. C. (2003). A simple rule for determining replenishment intervals of an inventory with linear decreasing demand rate. International Journal of Production Economics, 83, 139-142.
Hariga, M. (1994). The Inventory lot-sizing problem with continuous time-varying demand and shortages. Journal of Operational Research Society, 45(7), 827–837.
Hariga, M. (1995). Comparison of heuristic procedures for the inventory replenishment problem with a linear trend in demand. Computers & Industrial Engineering, 28(2).245-258.
Hariga, M. A. (1995). Effects of inflation and time-value of money on an inventory model with time-dependent demand rate and shortages. European Journal of Operational Research, 81, 512-520.
Henery, R. J. (1979). Inventory replenishment policy for increasing demand. Journal of the Operational Research Society, 30(7), 611-617.
Lagarias, J.C., Reeds, J. A., Wright, M. H., and Wright, P. E. (1998). Convergence properties of the nelder-mead simplex method in low dimensions. SIAM Journal of Optimization, 9(1), 112-147.
Lo, W. Y., Tsai, C. H., and Li, R. K. (2002). Exact solution of inventory replenishment policy for a linear trend in demand - two equation model. International Journal of Production Economics, 76, 111-120.
Moon, I., Giri, B. C., and Ko, B. (2005). Economic order quantity models for ameliorating/deterorating items under inflation and time discounting. European Journal of Operational Research, 162, 773-785.
Murdeshwar, T.M. (1988). Inventory replenishment policy for linearly increasing demand considering shortages - an optimal solution. Journal of Operational Research Society, 39(7), 687-692.
Nelder, J. A., and Mead, R. (1965). A simplex method for function minimization. Computer Journal, 7, 308-313.
Ritchie, E. (1984). The E.O.Q. for linear increasing demand: A simple optimal solution. Journal of the Operational Research, 35(10), 949-953.
Roger, M. H. (1996). Batching policies for a product life cycle. International Journal of Production Economics, 45, 421-427.
Schwarz, L. B. (1972). Economic order quantities for products with finite demand horizons. AIIE Transactions, 4(3), 234-237.
Silver, E. A. (1979). A simple inventory replenishment decision rule for a linear trend in demand. Journal of the Operational Research, 30, 71-75.
Teng, J. T. (1994). A note on inventory replenishment policy for increasing demand. Journal of the Operational Research, 45(11), 1335-1337.
Teng, J. T. (1996). A deterministic inventory replenishment model with a linear trend in demand. Operations Research Letters, 19, 33-41.
Teng, J. T., Chern, M. S., & Yang, H. L. (1997). An optimal Recursive method for various inventory replenishment models with increasing demand and shortages. Naval Research Logistics, 44, 791-806.
Theodore L. (1991). Exploit the product life cycle. Managing Product Life Cycle:From Start to Finish, Harvard Business School Press, 93-106.
Wang, S. P. (2002). On inventory replenishment with non-linear increasing demand. Computers and Operations Research, 29, 1819-1825.
Yang, J., and Rand, G. K. (1993). An analytic eclectic heuristic for replenishment with linear increasing demand. International Journal of Production Economics, 32, 261-266.
Yang, J., Zhao, G. Q., and Rand, G. K. (1999). Comparison of several heuristics using an analytical procedure for replenishment with nonlinear increasing demand. International Journal of Production Economics, 58, 49-55.
Yang, H. L., Teng, J. T., and Chern, M. S. (2002). A forward recursive algorithm for inventory lot-size models with power-form demand and shortages. European Journal of Operational Research, 137, 394-400.
Zhao, G. Q., Yang, J., and Rand, G. K. (2001). Heuristics for replenishment with linear decreasing demand. International Journal of Production Economics, 69, 339-345.

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