淡江大學覺生紀念圖書館 (TKU Library)
進階搜尋


下載電子全文限經由淡江IP使用) 
系統識別號 U0002-2101200910104500
中文論文名稱 允許延遲付款下零售商之最適訂購策略
英文論文名稱 The Retailer’s Optimal Ordering Policy Under Permissible Delay in Payments
校院名稱 淡江大學
系所名稱(中) 管理科學研究所博士班
系所名稱(英) Graduate Institute of Management Science
學年度 97
學期 1
出版年 98
研究生中文姓名 鄭美娟
研究生英文姓名 Mei-Chuan Cheng
電子信箱 891560046@s91.tku.edu.tw
學號 891560046
學位類別 博士
語文別 中文
口試日期 2009-01-10
論文頁數 113頁
口試委員 指導教授-歐陽良裕
共同指導教授-鄧進財
委員-林進財
委員-陳山火
委員-陳正綱
委員-張春桃
委員-曹銳勤
委員-歐陽良裕
中文關鍵字 存貨  有限補貨率  延遲付款  退化  模糊集合  符號距離 
英文關鍵字 Inventory  Finite replenishment rate  Permissible delay in payments  Deteriorating items  Fuzzy set  Signed distance 
學科別分類
中文摘要 延遲付款在實際商場交易行為中非常普遍,供應商經常以提供延遲付款的優惠吸引更多將延遲付款視為一種降價優惠的零售商。提供延遲付款對供應商而言,可吸引更多的零售商購買,並且也可降低同行之間削價競爭之惡性循環;對零售商而言,不僅減少資金的機會成本,在延遲付款期間,零售商還可利用銷售貨品的收入賺得利息。另外,生活中,常見貨品產生退化的現象。例如新鮮蔬果、醫療藥品、電子元件及汽油、酒精、香水等揮發性液體等,都可能會因為時間、溫度或環境等因素,產生變質、損壞或揮發等現象而使得庫存數量減少。所以,在探討此類貨品的存貨問題時,若不考慮退化的現象,將會做出不正確的決定而造成重大的損失。再者,關於允許延遲付款的存貨問題中,利息支付與利息賺得的計算是很重要的議題。過去探討延遲付款之存貨相關文獻大都假設支付利息的利率、賺得利息的利率及貨品退化率皆為固定常數。然而,在實際生活中,有很多因素會造成這三個參數產生不確定的情況。所以,我們考量以模糊數來處理此問題。
本論文探討允許延遲付款下零售商之存貨問題並進一步討論有限補貨率、貨品產生退化的現象、利率及貨品退化率不確定等議題且提供在不同問題下零售商的最適訂購策略。第一章說明研究動機與目的及相關文獻探討。第二章探討供應商提供零售商延遲付款優惠之存貨問題並考慮有限補貨率及兩種付款方法。第三章討論允許延遲付款及有限補貨率下零售商對退化性貨品之最適訂購策略。第四章進一步將利率及貨品退化率模糊化並建立允許延遲付款和訂購量有關的退化性貨品之模糊存貨系統。本論文建立兩個定理和兩個演算法,協助零售商在不同的存貨問題中決定最適訂購策略。同時,亦探討模型中參數值的變動對最適解的影響。最後,在第五章裡將上述各章所得的結論做一總結,並說明未來的研究方向。
英文摘要 A common phenomenon in the real market is that a supplier usually permits the retailer a delay of a fixed time period to settle the total amount owed to him. The permissible delay in payments produces benefits to the supplier. For example, it will attract some customers who consider it to be a type of price reduction and does not provoke competitors to reduce their prices and thus introduce lasting price reductions. Permissible delay in payments also provides advantages to the retailer due to the fact that the retailer can earn interest on the accumulated revenue received, and delay the payment up to the last moment of the permissible period allowed by the supplier. In addition, the deterioration of physical goods is common in daily life. For examples, the decay, damage or evaporation may occur during the normal storage period of items like fresh vegetables and fruit, pharmaceuticals, electronic component, gasoline, alcohol or perfumes. Consequently, the loss must be taken into account while developing the inventory models for such goods. Furthermore, the interest income and interest payments are important issues in the inventory problem associated with permissible delay in payments. Most studies related to permissible delay in payments assume that the interest rate is both fixed and predetermined. However, in the real market, many factors such as financial policy, monetary policy and inflation, may affect the interest rate. Moreover, within the environment of merchandise storage, some distinctive factors arise which ultimately affect the quality of products such as temperature, humidity, and storage equipment. Thus, the rate of interest charges, the rate of interest earned, and the deterioration rate in a real inventory problem may be fuzzy.
This thesis discusses the retailer’s inventory problems under some common phenomena including permissible delay in payments, finite replenishment rate, the deterioration of physical goods, fuzzy interest rate and fuzzy deterioration rate. Chapter 1 covers the motivation and objectives of this thesis. In this chapter, literature review about related research papers is also included. In Chapter 2, we establish an inventory model with a finite replenishment rate and permissible delay in payments under two different payment methods. Chapter 3 develops the deteriorating inventory model with a finite replenishment rate under permissible delay in payments. In Chapter 4, we discuss the problem that the rate of interest charges, the rate of interest earned, and the deterioration rate may be fuzzy and construct a fuzzy inventory system with deteriorating items under supplier credits linked to ordering quantity. In this dissertation, we develop two theorems and two algorithms to find the optimal ordering policy and provide numerical examples to illustrate the solution procedure. Also, sensitivity analysis is conducted for the parameters of the models. Finally, chapter 5 provides the conclusions of this thesis and some future research topics.
論文目次 目錄
頁次
表目錄 V
圖目錄 VI
使用符號一覽表 VII
第一章 緒論 1
1.1 研究動機與目的 1
1.2 相關文獻探討 3
1.2.1 延遲付款 3
1.2.2 有限補貨率 5
1.2.3 退化性貨品 7
1.2.4 模糊存貨模型 9
1.3 本文結構 11
第二章 允許延遲付款與兩種付款方法下之最適訂購策略 14
2.1 前言 14
2.2 符號說明與假設 15
2.3 模型的建立 16
2.3.1 付款方法一: 零售商僅支付已售出的貨品款項,利潤則保留移作他用 17
2.3.2 付款方法二: 零售商一有銷售收入便全數用以支付貨款,直到貨款全部付清 20
2.4 模型的求解 24
2.4.1 付款方法一: 零售商僅支付已售出的貨品款項,利潤則保留移作他用 25
2.4.2 付款方法二: 零售商一有銷售收入便全數用以支付貨款,直到貨款全部付清 28
2.5 特殊情況 33
2.5.1 允許延遲付款之EOQ模型 34
2.5.2 零售商於收到貨品時便立即付清貨款之EPQ模型 35
2.5.3 零售商於收到貨品時便立即付清貨款之EOQ模型 35
2.6 數值範例 36
2.7 小結 40
第三章 允許延遲付款下零售商對退化性貨品之最適訂購策略 41
3.1 前言 41
3.2 符號說明與假設 42
3.3 模型的建立 43
3.4 模型的求解 51
3.5 數值範例 57
3.6 小結 60
第四章 允許延遲付款和訂購量有關的退化性貨品之模糊存貨系統 62
4.1 前言 62
4.2 預備知識 63
4.3 符號說明與假設 68
4.4 模型的建立 69
4.4.1 回顧Chang et al.(2003)之模型 70
4.4.2 模糊存貨模型的建立 71
4.5 模型的求解 77
4.6 數值範例 87
4.7 討論 91
4.7.1 採用符號距離法而非重心法(centroid method)解模糊化的原因 91
4.7.2 模糊函數與確定型(crisp)函數之間的關係 92
4.8 小結 95
第五章 結論 97
5.1 主要研究結果 97
5.2 未來研究方向 99
附錄 證明單位時間存貨相關總成本TRC1-1(T)對T的二階微分在點T=T1-1大於零 102
參考文獻 103

表目錄
頁次
表1-1允許延遲付款下存貨模型比較表 11
表2-1參數s和h的敏感性分析 38
表2-2不同利率值下之最適解 39
表3-1Ie、S及θ分別在不同參數值下之最適解 59
表4-1 不同訂購成本S下之最適解 87
表4-2不同允許延遲付款之最小訂購量Qd之最適解 88
表4-3不同延遲付款的期限M下之最適解 89
表4-4不同的(△*, △**)值下之最適解 90


圖目錄
頁次
圖1-1 本文結構流程圖 13
圖 2-1 零售商的存貨水準與產生利息的累積銷售量示意圖 18
圖 3-1 零售商存貨水準與時間的關係圖 43

參考文獻 參考文獻
[1] Aggarwal, S. P. and Jaggi, C. K. (1989). Ordering policy for decaying inventory. International Journal of Systems Science, 20(1), 151-155.
[2] Aggarwal, S. P. and Jaggi, C. K. (1995). Ordering policies of deteriorating items under permissible delay in payments. Journal of the Operational Research Society, 46(5), 658-662.
[3] Chang, C. T. (2004). An EOQ model with deteriorating items under inflation when supplier credits linked to order quantity. International Journal of Production Economics, 88(3), 307-316.
[4] Chang, C. T., Ouyang L. Y. and Teng J. T. (2003). An EOQ model for deteriorating items under supplier credits linked to ordering quantity. Applied Mathematical Modelling, 27(12), 983-996.
[5] Chang, C. T. and Teng, J. T. (2004). Retailer’s optimal ordering policy under supplier credits. Mathematical Methods of Operations Research, 60(3), 471-483.
[6] Chang, C. T. and Wu, S. J. (2003). A note on ‘optimal payment time under permissible delay in payment for products with deterioration’. Production Planning and Control, 14(5), 478-482.
[7] Chang, H. C. (2004). An application of fuzzy sets theory to the EOQ model with imperfect quality items. Computers and Operations Research, 31(12), 2079-2092.
[8] Chang, P. T., Yao, M. J., Huang, S. F. and Chen, C. T. (2006). A genetic algorithm for solving a fuzzy economic lot-size scheduling problem. International Journal of Production Economics, 102(2), 265-288.
[9] Chang, H. C., Yao, J. S. and Ouyang, L. Y. (2004). Fuzzy mixture inventory model with variable lead-time based on probabilistic fuzzy set and triangular fuzzy number. Mathematical and Computer Modelling, 39(2-3), 287-304.
[10] Chang, H. C., Yao, J. S. and Ouyang, L. Y. (2006). Fuzzy mixture inventory model involving fuzzy random variable lead-time demand and fuzzy total demand. European Journal of Operational Research, 169(1), 65-80.
[11] Chapman, C. B., Ward, S. C., Cooper, D. F. and Page, M. J. (1984). Credit policy and inventory control. Journal of the Operational Research Society, 35(12), 1055-1065.
[12] Chen, L. H. and Ouyang, L. Y. (2006). Fuzzy inventory model for deteriorating items with permissible delay in payment. Applied Mathematics and Computation, 182(1), 711-726.
[13] Chen, S. H. and Wang, C. C. (1996). Backorder fuzzy inventory model under functional principle. Information Sciences, 95(1-2), 71-79.
[14] Chen, S. H., Wang, S. T. and Chang, S. M. (2005). Optimization of fuzzy production inventory model with repairable defective products under crisp or fuzzy production quantity. International Journal of Operations Research, 2(2), 31-37.
[15] Chun, Y. H. (2003). Optimal pricing and ordering policies for perishable commodities. European Journal of Operational Research, 144(1), 68-82.
[16] Chung, K. J., Goyal, S. K. and Huang, Y. F. (2005). The optimal inventory policies under permissible delay in payments depending on the ordering quantity. International Journal of Production Economics, 95(2), 203-213.

[17] Chung, K. J. and Huang, Y. F. (2003). The optimal cycle time for EPQ inventory model under permissible delay in payments. International Journal of Production Economics, 84(3), 307-318.
[18] Chung, K. J. and Liao, J. J. (2004). Lot-sizing decisions under trade credit depending on the ordering quantity. Computers and Operations Research, 31(6), 909-928.
[19] Cohen, M. A. (1977). Joint pricing and ordering policy for exponentially decaying inventory with known demand. Naval Research Logistics Quarterly, 24(2), 257-268.
[20] Covert, R. P. and Philip, G. C. (1973). An EOQ model for items with Weibull distribution deterioration. AIIE Transactions, 5(4), 323-326.
[21] Dave, U. (1985). On “economic order quantity under conditions of permissible delay in payments” by Goyal. Journal of the Operational Research Society, 36(11), 1069.
[22] Dave, U. and Patel, L. K. (1981). policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society, 32(2), 137-142.
[23] Davis, R. A. and Gaither, N. (1985). Optimal ordering policies under conditions of extended payment privileges. Management Science, 31(4), 499-509.
[24] Dye, C. Y., Chang, H. J. and Teng, J. T. (2006). A deteriorating inventory model with time-varying demand and shortage- dependent partial backlogging. European Journal of Operational Research, 172(2), 417-429.
[25] Dye, C. Y. (2007). Joint pricing and ordering policy for a deteriorating inventory with partial backlogging. Omega, 35(2), 184-189.
[26] Gen, M., Tsujimura, Y. and Zheng, P. Z. (1997). An application of fuzzy set theory to inventory control models. Computers and Industrial Engineering, 33(3-4), 553-556.
[27] Ghare, P. M. and Schrader, G. H. (1963). A model for exponentially decaying inventory system. Journal of Industrial Engineering, 14(5), 238-243.
[28] Goyal, S. K. (1985). Economic order quantity under conditions of permissible delay in payments. Journal of the Operational Research Society, 36(4), 335-338.
[29] Goyal, S. K. and Giri, B. C. (2001). Recent trends in modeling of deteriorating inventory. European Journal of Operational Research, 134(1), 1-16.
[30] Goyal, S. K., Teng, J. T. and Chang, C. T. (2007). Optimal ordering policies when the supplier provides a progressive interest scheme. European Journal of Operational Research, 179(2), 404-413.
[31] Hadley, G. and Whitin, T. M. (1961). An optimal final inventory model. Management Science, 7(2), 179-183.
[32] Haley, C. W. and Higgins, R. C. (1973). Inventory policy and trade credit financing. Management Science, 20(4), 464-471.
[33] Harris, F. W. (1913). How many parts to make at once. Factory, The Magazine of Management, 10(2), 135-136.
[34] Hillier, F. S. and Lieberman, G. J. (2005). Introduction to Operations Research (8th edition), McGraw-Hill, Inc. New York.
[35] Huang, Y. F. (2003). Optimal retailer’s ordering policies in the EOQ model under trade credit financing. Journal of the Operational Research Society, 54(9), 1011-1015.
[36] Huang, Y. F. (2004). Optimal retailer’s replenishment policy for the EPQ model under the supplier’s trade credit policy. Production Planning and Control, 15(1), 27-33.
[37] Hwang, H. and Shinn, S. W. (1997). Retailer’s pricing and lot sizing policy for exponentially deteriorating products under the condition of permissible delay in payments. Computers and Operations Research, 24(6), 539-547.
[38] Ishii, H. and Konno, T. (1998). A stochastic inventory with fuzzy shortage cost. European Journal of Operational Research, 106(1), 90-94.
[39] Jamal, A. M. M., Sarker, B. R. and Wang, S. (1997). An ordering policy for deteriorating items with allowable shortage and permissible delay in payment. Journal of the Operational Research Society, 48(8), 826-833.
[40] Jamal, A. M. M., Sarker, B. R. and Wang, S. (2000). Optimal payment time for a retailer under permitted delay of payment by the wholesaler. International Journal of Production Economics, 66(1), 59-66.
[41] Kaufmann, A. and Gupta, M. M. (1991). Introduction to Fuzzy Arithmetic: Theory and Applications, Van Nostrand Reinhold, New York, pp. 3-5.
[42] Kingsman, B. G. (1983). The effect of payment rules on ordering and stocking in purchasing. Journal of the Operational Research Society, 34(11), 1085-1098.
[43] Lee, H. M. and Yao, J. S. (1999). Economic order quantity in fuzzy sense for inventory without backorder model. Fuzzy Sets and Systems, 105(1), 13-31.


[44] Liao, H. C., Tsai, C. H. and Su, C. T. (2000). An inventory model with deteriorating items under inflation when a delay in payment is permissible. International Journal of Production Economics, 63(2), 207-214.
[45] Maiti, M. K. (2008). Fuzzy inventory model with two warehouses under possibility measure on fuzzy goal. European Journal of Operational Research, 188(3), 746-774.
[46] Mandal, B. N. and Phaujdar, S. (1989a). Some EOQ models under permissible delay in payments. International Journal of Management Science, 5(2), 99-108.
[47] Mandal, B. N. and Phaujdar, S. (1989b). An inventory model for deteriorating items and stock-dependent consumption rate. Journal of the Operational Research Society, 40(5), 483-488.
[48] Misra, R. B. (1975). Optimum production lot size model for a system with deteriorating inventory. International Journal of Production Economics, 13(5), 495-505.
[49] Nahmias, S. (1978). Perishable inventory theory: a review. Operations Research, 30(4), 680-708.
[50] Ouyang, L. Y., Chang, C. T. and Teng, J. T. (2005a). An EOQ model for deteriorating items under trade credits, Journal of the Operational Research Society, 56(6), 719-726.
[51] Ouyang, L. Y., Teng, J. T., Chuang, K. W. and Chuang, B. R. (2005b). Optimal inventory policy with noninstantaneous receipt under trade credit. International Journal of Production Economics, 98(3), 290-300.
[52] Ouyang, L. Y., Teng, J. T. and Chen, L. H. (2006a). Optimal ordering policy for deteriorating items with partial backlogging under permissible delay in payments. Journal of Global Optimization, 34(2), 245-271.
[53] Ouyang, L. Y., Wu, K. S. and Ho, C. H. (2006b). Analysis of optimal vendor-buyer integrated inventory policy involving defective items. International Journal of Advanced Manufacturing Technology, 29(11-12), 1232-1245.
[54] Ouyang, L. Y., Wu, K. S. and Yang, C. T. (2006c). A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Computers and Industrial Engineering, 51(4), 637-651.
[55] Ouyang, L. Y., Wu K. S. and Yang, C. T. (2008). Retailer’s ordering policy for non-instantaneous deteriorating items with quantity discount, stock-dependent demand and stochastic backorder rate. Journal of the Chinese Institute of Industrial Engineers, 25(1), 62-72.
[56] Padmanabhan, G. and Vrat, P. (1990a). An EOQ model for items with stock dependent consumption rate and exponential decay. Engineering Costs and Production Economics, 18(3), 241-246.
[57] Padmanabhan, G. and Vrat, P. (1990b). Inventory model with a mixture of back orders and lost sales. International Journal of Systems Science, 21(8), 1721-1726.
[58] Pal, A. K., Bhunia, A. K. and Mukherjee, R. N. (2006). Optimal lot size model for deteriorating items with demand rate dependent on displayed stock level (DSL) and partial backordering. European Journal of Operational Research, 175(2), 977-991.
[59] Papachristos, S. and Skouri, K. (2000). An optimal replenishment policy for deteriorating items with time-varying demand and partial-exponential type–backlogging. Operations Research Letters, 27(4), 175-184.


[60] Papachristos, S. and Skouri, K. (2003). An inventory model with deteriorating items, quantity discount, pricing and time-dependent partial backlogging. International Journal of Production Economics, 83(3), 247-256.
[61] Pertrovic, D. and Sweeney, E. (1994). Fuzzy knowledge-based approach to treating uncertainty in inventory control. Computer Integrated Manufacturing Systems, 7(3), 147-152.
[62] Philip, G. C. (1974). A generalized EOQ model for items with Weibull distribution. AIIE Transactions, 6(2), 159-162.
[63] Roy, T. K. and Maiti, M. (1997). A fuzzy EOQ model with demand-dependent unit cost under limited storage capacity. European Journal of Operational Research, 99(2), 425-432.
[64] Sachan, R. S. (1984). On inventory policy model for deteriorating items with time proportional demand. Journal of the Operational Research Society, 35(11), 1013-1019.
[65] Sana, S. and Chaudhuri, K. S. (2003). An EOQ model with time-dependent demand, inflation and money value for a ware-house enterpriser. Advanced Modeling and Optimization, 5(2), 135-146.
[66] Sarker, B. R., Jamal, A. M. M. and Wang, S. (2000). Optimal payment time under permissible delay in payment for products with deterioration. Production Planning and Control, 11(4), 380-390.
[67] Sarker, B. R., Mukherjee, S. and Balan, C. V. (1997). An order-level lot size inventory model with inventory-level dependent demand and deterioration. International Journal of Production Economics, 48(3), 227-236.

[68] Shah, N. H. (1993). Probabilistic time-scheduling model for an exponentially decaying inventory when delays in payments are permissible. International Journal of Production Economics, 32(1), 77-82.
[69] Shah, Y. K. (1977). An order-level lot-size inventory model for deteriorating items. AIIE Transactions, 9(1), 108-112.
[70] Silver, E. A., Pyke, D. F. and Peterson, R. (1998). Inventory Management and Production Planning and Scheduling (3rd edition), John Wiley & Sons.
[71] Stevenson, W. J. (1996). Production/Operations Management, Von Hoffman Press, New York.
[72] Tadikamalla, P. R. (1978). An EOQ inventory model for items with gamma distributed deterioration. AIIE Transactions, 10(1), 100-103.
[73] Taylor III, B. W. (1999). Introduction to Management Science, Prentice-Hall, Englewood-Cliffs, NJ.
[74] Teng, J. T. (2002). On the economic order quantity under conditions of permissible delay in payments. Journal of the Operational Research Society, 53(8), 915-918.
[75] Teng, J. T., Chang, C. T., Chern, M. S. and Chan, Y. L. (2007). Retailer’s optimal ordering policies with trade credit financing. International Journal of Systems Science, 38(3), 269-278.
[76] Teng, J. T., Chang, C. T. and Goyal, S. K. (2005). Optimal pricing and ordering policy under permissible delay in payments. International Journal of Production Economics, 97(2), 121-129.
[77] Teng, J. T., Ouyang, L. Y. and Chen, L. H. (2006). A comparison between two pricing and lot-sizing models with partial backlogging and deteriorated items. International Journal of Production Economics, 105(1), 190-203.
[78] Vrat, P. and Padmanabhan, G. (1990). An inventory model under inflation for stock dependent consumption rate items. Engineering Costs and Production Economics, 19(1-3), 379-383.
[79] Vujosevic, M., Petrovic, D. and Petrovic, R. (1996). EOQ formula when inventory cost is fuzzy. International Journal of Production Economics, 45(1-3), 499-504.
[80] Wang, S. P. (2002). An inventory replenishment policy for deteriorating items with shortages and partial backlogging. Computers and Operations Research, 29(14), 2043-2051.
[81] Wu, K. S., Ouyang, L. Y. and Yang, C. T. (2006). An optimal replenishment policy for non-instantaneous deteriorating items with stock-dependent demand and partial backlogging, International Journal of Production Economics, 101(2), 369-384.
[82] Yang, H. L. (2005). A comparison among various partial backlogging inventory lot-size models for deteriorating items on the basis of maximum profit. International Journal of Production Economics, 96(1), 119-128.
[83] Yao, M. J., Chang, P. T. and Huang, S. F. (2005). On the economic lot scheduling problem with fuzzy demands. International Journal of Operations Research, 2(2), 58-71.
[84] Yao, J. S., Chang, S. C. and Su, J. S. (2000). Fuzzy inventory without backorder for fuzzy quantity and fuzzy total demand quantity. Computers and Operations Research, 27(10), 935-962.
[85] Yao, J. S., Huang, W. T. and Huang, T. T. (2007). Fuzzy flexibility and product variety in lot-sizing. Journal of Information Science and Engineering, 23(1), 49-70.

[86] Yao, J. S. and Lee, H. M. (1999). Fuzzy inventory with or without backorder for fuzzy order quantity with trapezoid fuzzy number. Fuzzy Sets and Systems, 105(3), 311-337.
[87] Yao, J. S. and Wu, K. (2000). Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets and Systems, 116(2), 275-288.
[88] Zhou, Y. W. and Lau, H. S. (2000). An economic lot-size model for deteriorating items with lot-size dependent replenishment cost and time-varying demand. Applied Mathematical Modelling, 24(10), 761-770.
[89] Zimmermann, H. J. (1996). Fuzzy Set Theory and its Applications (3rd edition), Kluwer Academic Publishers, Dordrecht.
[90] 高孔廉(1985)。作業研究-管理決策之數量方法。第四版,台北市:三民書局。
[91] 顏憶茹、張淳智(2001)。物流管理:原理、方法與實例3/e。台北縣:前程企業管理有限公司。
論文使用權限
  • 同意紙本無償授權給館內讀者為學術之目的重製使用,於2009-02-13公開。
  • 同意授權瀏覽/列印電子全文服務,於2009-02-13起公開。


  • 若您有任何疑問,請與我們聯絡!
    圖書館: 請來電 (02)2621-5656 轉 2281 或 來信