臺灣人文及社會科學引文索引資料庫系統

:::

詳目顯示

回上一頁
第 1 筆 / 總合 1 筆   第一頁 上一頁 下一頁 最後一頁
/1頁
題名：可控制前置時間的一些隨機性存貨模型之研究
作者：莊博仁
作者(外文)：Bor-Ren Chuang
校院名稱：淡江大學
系所名稱：管理科學學系
指導教授：歐陽良裕
學位類別：博士
出版日期：1999
主題關鍵詞：存貨；前置時間；趕工成本；inventory；lead time；crashing cost
原始連結：連回原系統網址new window
相關次數：
  • 被引用次數被引用次數:期刊(1) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:1
  • 共同引用共同引用:0
  • 點閱點閱:69
在企業體的存貨管理決策中，前置時間的控制愈來愈受重視，同時也是很多學者感興趣的一個主題。以往有關存貨問題的相關學術典籍或研究文獻大多將前置時間視為已知且不可控制的常數或隨機變數，晚近已有很多學者對不可控制的前置時間開始產生質疑，進而著手探討連續性檢查訂購策略下的可控制前置時間；然而其研究焦點幾乎集中在尋找最適的前置時間與訂購數量，忽略了請購點也是控制存貨成本的一個重要因子。因此，本文試圖對於連續性訂購策略構建一些適用於不同存貨環境下的計量模型，並同時找出最適的訂購量、前置時間與請購點。另一方面，環顧現有的文獻典籍，在存貨理論中另一頗為實用的週期性檢查訂購策略，其對於控制前置時間的研究卻少有學者投入鑽研行列；本文亦將對週期性檢查的存貨系統探討最適的訂購策略。
本論文係針對可控制的前置時間分別於連續和週期性檢查訂購策略下，各提出五個隨機性存貨管理數學模型。在第二和第三章的連續性檢查存貨模型中，訂購量、前置時間與請購點均設為決策變數，且在缺貨期間，我們考慮下列四種模型： (1)缺貨成本項包含在目標函數中的常態需求模型、 (2)缺貨成本項包含在目標函數中的分配不拘需求模型(即前置時間內需求量的機率分配型式為未知)、 (3)缺貨成本項以服務水準限制式替代的常態需求模型、 (4)缺貨成本項以服務水準限制式替代的分配不拘需求模型。另一方面，為冀盼本論文的發展能契合實際的存貨需求，我們更深入探討有關到貨品項中含有瑕疵品、數量折扣和隨機欠撥率等常見但於一般典籍文獻所見不多的存貨問題。
其次，相對於連續性檢查存貨模型，在第四章中，我們提出四個可控制前置時間的週期性檢查存貨模型，即考量缺貨時，缺貨成本項包含在目標函數中及以服務水準限制式替代的常態需求模型與分配不拘需求模型，其中檢查週期與前置時間視為決策變數。最後，架構在第四章的基礎上，我們在第五章進一步鋪陳 (T,R,L) 模型，建立更適合真實存貨行為的計量模型；由數值運算結果顯示，此一新模型較第四章的 (T,L) 模型更能提供較大的成本節省空間以及較優的服務水準。此外，對於文中第二章與第四章所建構的基本數學模型，我們都將進行敏感性分析並作經濟上之解說。
In inventory managerial strategies for a business enterprise, lead time plays an increasingly important role on the applications of business activities, and also has been a topic of interest for many researchers. In most of the early literature dealing with the inventory problems, either in deterministic or probabilistic model, lead time is always treated as a prescribed constant or a random variable. Recently, many researchers felt doubtful about the uncontrollability of lead time and further embarked on the analysis of controllable lead time associated with the continuous review ordering policy. However, their research conceptions are almost concentrated on solving the optimal order quantity and lead time but ignoring the fact that the effects of reorder point is also an important factor in inventory cost control. Therefore, for the continuous review ordering policy, we attempt to formulate some quantitative mathematical models to accommodate the different inventory features, and simultaneously optimize order quantity, lead time and reorder point. On the other hand, viewing the domain of the periodic review inventory policies, existing literature discussing the controllable lead time problems is quite few. For this reason, this thesis seeks to investigate the effects of lead time on the periodic review inventory model. And hence, another purpose in this thesis is to examine the periodic review inventory systems so as to look for their corresponding optimal ordering strategies.
This thesis mainly focuses on the controllable lead time for the continuous and periodic review ordering policies. Under both of these two policies, we respectively propose five stochastic inventory mathematical models. In chapters 2 and 3, continuous review policy, order quantity, lead time and reorder point are viewed as decision variables. During the stockout period, four cases are considered: 1) Stockout cost term is included in the objective function for the normal demand model, 2) Stockout cost term is included in the objective function for the distribution free demand model (i.e., the probability distribution of lead time demand is unknown), 3) Instead of having a stockout cost term in the objective function, a service level constraint is taken into consideration for the normal demand model, and 4) Instead of having a stockout cost term in the objective function, a service level constraint is taken into consideration for the distribution free demand model. On the other hand, in order to fit the practical inventory demands, we further consider several general inventory problems in the real world but they seldom appear in the research literature, e.g. an arrival order lot containing defective items, quantity discounts and stochastic backorder rate.
Additionally, for the periodic review inventory models in chapter 4, we present four models to analyze the controllable lead time. Namely, we consider two demand models that are normal and distribution free. Both of these models respectively involve two cases that stockout cost term is included in the objective function and stockout cost term in the objective function is replaced by a service level constraint, where review period and lead time are allowed as decision variables. Finally, based upon the framework of chapter 4, we further establish a (T,R,L) model in chapter 5 to agree with a more realistic behavior pattern of quantitative model. From numerical example provided, it indicates that this new (T,R,L) model can achieve a significant amount of savings and provide a higher service level than that in (T,L) model of chapter 4. Furthermore, for the formulated mathematical inventory models in chapter 2 and 4, we analyze the effects of parameters and give economic interpretation of the circumstances.
[1] Ben-Daya, M. and Raouf, A. (1994), "Inventory Models Involving Lead Time as Decision Variable", Journal of the Operational Research Society, Vol. 45, No. 5, pp. 579-582.new window
[2] Brown, R. G. (1967), Decision Rules for Inventory Management, Holt, Rinehart, and Winston, New York.
[3] Candace, A. Y. (1987), "Planned Leadtimes for Serial Production System", IIE Transactions, Vol. 19, No. 3, pp. 300-307.
[4] Chiu, H. N. (1995), "A Heuristic Periodic Review Perishable Inventory Model with Lead Times", International Journal of Production Economics, Vol. 42, pp. 1-15.
[5] Das, C. (1975), "Effect of Lead Time on Inventory: a Static Analysis", Operational Research Quarterly, Vol. 26, pp. 273-282.
[6] Foote, B., Kebriaei, N., and Kumin, H. (1988), "Heuristic policies for Inventory Ordering Problems with Long and Randomly Varying Lead time", Journal of Operations Management, Vol. 7, pp. 115-124.
[7] Gallego, G. and Moon, I. (1993), "The Distribution Free Newsboy Problem : Review and Extensions", Journal of the Operational Research Society, Vol. 44, No. 8, pp. 825-834.
[8] Hadley, G. and Whitin, T. M. (1963), Analysis of Inventory System, Prentice-Hall, Englewood Cliffs, New York.
[9] Johnson, L. A. and Montgomery, D. C. (1974), Operations Research in Production Planning, Scheduling, and Inventory Control, John Wiley & Sons, New York.
[10] Kalro, A. H. and Gohil, M. M. (1982), "A Lot Size Model with Backlogging when the Amount Received is Uncertain", International Journal of Production Research, Vol. 20, No. 6, pp. 775-786.
[11] Kim, D. H. and Park, K. S. (1985), " Inventory Model with a Mixture of Lost Sales and Time Weighted Backorders", Journal of the Operational Research Society, Vol. 36, No. 3, pp. 231-238.
[12] Liao, C. J. and Shyu, C. H. (1991), "An Analytical Determination of Lead Time with Normal Demand", International Journal of Operations Production Management, Vol. 11, No. 9, pp. 72-78.
[13] Liberatore, M. (1977), "Planning Horizons for A Stochastic Lead Time Model", Operations Research, Vol. 25, No, 6, pp. 977-988.
[14] Monden, Y. (1983), Toyota Production System, Institute of Industrial Engineers, Norcross, Georgia.
[15] Montgomery, D. C., Bazaraa, M. S., and Keswani, A. K. (1973), "Inventory Models with a Mixture of Backorders and Lost Sales", Naval Research Logistics, Vol. 20, pp. 255-263.
[16] Moon, I. and Gallego, G. (1994), "Distribution Free Procedures for Some Inventory Models", Journal of the Operational Research Society, Vol. 45, No. 6, pp. 651-658.
[17] Naddor, E. (1966), Inventory System, John Wiley, New York.
[18] Ouyang, L. Y., Yeh, N. C., and Wu, K. S. (1996), "Mixture Inventory Model with Backorders and Lost Sales for Variable Lead Time", Journal of the Operational Research Society, Vol. 47, No. 6, pp. 829-832.
[19] Ouyang, L. Y. and Wu, K. S. (1997), "Mixture Inventory Model Involving Variable Lead Time with a Service Level Constraint", Computers and Operations Research, Vol. 24, No. 9, pp. 875-882.
[20] Ouyang, L. Y. and Wu, K. S. (1998), "A Minimax Distribution Free Procedure for Mixed Inventory Model Involving Variable Lead Time", International Journal of Production Economics, Vol. 56-57, pp. 511-516.
[21] Paknejad, M. J., Nasri, F., and Affisco, J. F. (1995), "Defective units in a continuous in a continuous review system", International Journal of Production Research, Vol. 33, No. 10, pp. 2767-2777.
[22] Sarker, B. R. and Coates, E. R. (1997), "Manufacturing Setup Cost Reduction under Variable Lead Time and Finite Opportunities for Investment", International Journal of Production Economics, Vol. 49, pp. 237-247.
[23] Schwaller, R, L. (1988), "EOQ under Inspection Costs", Production and Inventory Management Journal, Third Quarter, pp. 22-24.
[24] Shih, W. (1980), "Optimal Inventory Policies when Stockouts Result from Defective Products", International Journal of Production Research, Vol. 18, No. 6, pp. 677-686.
[25] Silver, E. A. (1976), "Establishing the Order Quantity when the Amount Received is Uncertain", INFOR, Vol. 14, pp. 32-39.
[26] Silver, E. A. and Peterson, R. (1985), Decision Systems for Inventory Management and Production Planning, John Wiley, New York.
[27] Subramanyam, E. S. and Kumaraswamy, S. (1981), "EOQ Formula under Varying Marketing Policies and Conditions", IIE Transactions, Vol. 19, No. 13, pp. 312-314.
[28] Taylor III, B. W. (1996), Introduction to Management Science, Prentice Hall, New Jersey.
[29] Tersine, R. J. (1982), Principles of Inventory and Materials Management, North Holland, New York.
[30] Tersine, R. J. (1994), Principles of Inventory and Materials Management,
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
QR Code
QRCODE

臺灣人文及社會科學引文索引資料庫

目前上線人數：713（臺灣：711，外國：2） ／ 本年度總使用人次：2564847 ／ 訪客人次（自102年09月）：68362936
國家圖書館著作權聲明 Copyright © 2013 All rights reserved.
本館地址: 100201臺北市中山南路20號． 本館地圖及交通資訊．
總機：(02)23619132．最佳瀏覽解析度為1024x768以上