運用聯合補貨與通路協調在供應鏈合作之最佳化

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姓名

陳宗輝(Tsung-Hui Chen) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

運用聯合補貨與通路協調在供應鏈合作之最佳化
(Optimizing supply chain collaboration based on joint replenishment and channel coordination)

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摘要(中)

本研究所探討的問題主要有三個方向：一、提出聯合補貨與通路協調的機制，分析其對供應鏈系統成本改善所產生的影響。二、整合聯合補貨、通路協調以及損耗性商品管理等問題。三、針對多產品、多階層的供應鏈系統，探討如何使得整體通路的利潤最大化。在第一類問題中，我們建構了多個由單一製造商提供多項同質性商品給單一零售商的模式，而其中這些商品共用同一個生產設備。這些模式介紹了如何在供應鏈系統中來整合多產品、多階層的生產及補貨，並運用數量折扣的方式來達到製造商與零售商之間的雙贏目標。在第二類問題中同樣考慮單一製造商、單一零售商以及多產品的通路系統。在這樣的環境設定下，我們加入了產品具有損耗及其需求隨時間變化等特性，發展了四個不同的生產及補貨模式來分析通路協調和聯合補貨對系統成本所產生的影響。第三類問題則是將第二類問題中的通路系統加入了產品定價的議題，探討不同的生產及定價模式如何使得整體系統利潤最大化。

摘要(英)

This thesis deals with three areas of emerging research: proposing a joint replenishment program coupled with a channel coordination practice, integrating the three streams of, as yet, rather disjointed research works: namely joint replenishment programs (JRP); channel coordination; and deteriorating goods management, and developing the profit-maximization models, with key features of partially controllable demand rates through pricing scheme and exponentially decaying deterioration rates for the products. In first area, we formulated several supply chain models, with a manufacturer supplying a family of products to a retailer, and the products sharing a common production facility. The models illustrate the challenge of integrating multi-items with multi-echelon production and replenishment, and a saving-sharing mechanism, through a quantity discount scheme, is proposed so that Pareto improvements (i.e., one party is better off and the other is no worse off) can be achieved among channel participants. In second area, the scenario of multi-product and multi-echelon supply chain, which produces, distributes, and sells deteriorating goods in the marketplace has been considered. Under this framework, four cost models were developed, with key assumptions related to time-proportional demand and exponentially decaying deterioration rates. The decision models in third area adopt the supply-side cost control mechanism, namely joint replenishment program and channel coordination practice, and the demand-side pricing scheme. Under a structured framework, four profit-maximization models were developed, with key features of partially controllable demand rates through pricing scheme and exponentially decaying deterioration rates for the products. These models, representing various replenishment and production policies, offer qualitative insights into the interplay between channel coordination and joint replenishment mechanisms.

關鍵字(中)

★ 損耗性商品
★ 運籌管理
★ 通路協調
★ 聯合補貨
★ 供應鏈
★ 定價

關鍵字(英)

★ Transportation
★ Channel coordination
★ Pareto improvements
★ Pricing
★ Logistics
★ Supply chain
★ Joint replenishment
★ Deterioration

論文目次

Contents
Chinese Abstract ................................................................................................I
English Abstract ............................................................................................... II
Contents ...……............................................................................................... III
List of Figures ................................................................................................... V
List of Tables ……………………………………………………...…..…….VII
1. Introduction .................................................................................................1
2. Literature Review .......................................................................................9
3. Managing the non-deteriorating goods …………….…………………..14
3.1 The non-cooperative policy ……………………………..…………….….………..18
3.1.1 Individual item non-cooperative replenishment (policy I) …………..………..18
3.1.2 Joint item non-cooperative replenishment (policy II) …………….….……….19
3.2 The cooperative policy ………..……………………………………….….……….20
3.2.1 Individual item cooperative replenishment (policy III) …….……….………..20
3.2.2 Joint item cooperative replenishment (policy IV) ……………….…..………..21
3.3 Search algorithm ……...…………………………...………………….……………22
3.4 Numerical study …………………………...…...……………………….………….23
4. Managing the deteriorating goods …………..…………..……….……..31
4.1 The decentralized policies ………………………………………………….………34
4.2 The centralized policies …………………………………………………….………38
4.3 Numerical study ……...…………………………………………………….………39
4.3.1 Impact of rates of deterioration ……………………………………….………40
4.3.2 Impact of retailer’s purchase cost …………………………………….………42
4.3.3 Sensitivity analysis………………………………………………….….……...45
5. The profit-maximization models for the deteriorating goods ………..48
5.1 The decentralized policies ………….……………………………...……….………51
5.1.1 Individual item non-cooperative replenishment (policy I) ………………..…..51
5.1.2 Joint item non-cooperative replenishment (policy II) …………..…........…….54
5.2 The centralized policies …………..….……………..…………………...….………54
5.2.1 Individual item cooperative replenishment (policy III) ……...……….………55
5.2.2 Joint item cooperative replenishment (policy IV) …………………….……….56
5.3 A linear demand case ………………………………………………………………56
5.3.1 Optimal property ………………………………………………………………56
5.3.2 Search procedure ………………………………………………………………57
5.4 Numerical example …………………………………………………………………58
6. Conclusion and future work …………………………………………....66
7. Reference ……….. …………………………………………....................68
8. Appendix …………………………………………...................................76
About the author………………………………………...................................80

參考文獻

Abad, P.L., 1996. Optimal pricing and lot-sizing under conditions of perishability and partial backordering, Management Science 42, 1093-1104.
Abdul-Jalbar, B., Gutiérrez, J., Puerto, J., Sicilia, J., 2003. Policies for inventory/distribution systems: the effect of centralization vs. decentralization. International Journal of Production Economics 81-82 (1), 281-293.
Aksoy, Y., Erenguc, S.S., 1988. Multi-item inventory models with co-ordinated replenishments: a survey. International Journal of Operations & Production Management 8 (1), 63-73.
Axsäter, S., Zhang, W.F., 1999. A joint replenishment policy for multi-echelon inventory control. International Journal of Production Economics 59 (1-3), 243-250.
Bahari-Kashani, H., 1989. Replenishment schedule for deteriorating items with time- proportional demand. Journal of the Operational Research Society 40, 75-81.
Banerjee, A., 1986. A joint economic-lot-size model for purchaser and vendor. Decision sciences 17 (3), 292-311.
Banerjee, A., Banerjee, S., 1992. Coordinated, orderless inventory replenishment for a single supplier and multiple buyers through electronic data interchange. International Journal of Technology Management 7 (4/5), 328-336.
Banerjee, A., Kim, S., 1995. An integrated JIT inventory model. International Journal of Operations & Production Management 15 (9), 237-244.
Benjamin, J., 1989. An analysis of inventory and transportation costs in a constrained network. Transportation Science 23 (3), 177-183.
Ben-Khedher, N., Yano, C.A., 1994. The multi-item joint replenishment problem with transportation and container effects. Transportation Science 28 (1), 37-54.
Blumenfeld, D.E., Burns, L.D., Daganzo, C.F., 1991. Synchronizing production and transportation schedules. Transportation Research Part B: Methodological 25B (1), 23-37.
Bose, S., Goswami, A., Chaudhuri, K.S., 1995. An EOQ model for deteriorating items with linear time-dependent demand rate and shortages under inflation and time discounting. Journal of the Operational Research Society 46, 771-782.
Boyd, E.A., Bilegan, I.C., 2003. Revenue management and e-commerce. Management Science 49, 1363-86.
Callioni, G., Billington, C., 2001. Supply chain management - effective collaboration [online]. Operations Research/Management Science Today. Available from: http://www.lionhrtpub.com/orms [Accessed 2 March 2004].
Carreno, J.J., 1990. Economic lot scheduling for multiple products on parallel identical processors. Management Science 36 (3), 348-358.
Cetinkaya, S., Lee, C.Y., 2000. Stock replenishment and shipment scheduling for vendor-managed inventory systems. Management Science 46 (2), 217-232.
Cohen, M.A., 1977. Joint pricing and ordering policy for exponentially decaying inventory with know demand, Naval Research Logistics Quarterly 24, 257-268.
Covert, R.P., Philip, G.C., 1973. An EOQ model for items with Weibull distribution deterioration. AIIE Transactions 5, 323-326.
Das, C., Goyal, S.K., 1991. Economic ordering policy for deterministic two-echelon distribution systems. Engineering Costs and Production Economics 21, 227-231.
Dave, U., Patel, L.K., 1981. (T, Si) Policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society 32, 137-142.
Dobson, G., 1987. The economic lot-scheduling problem: achieving feasibility using time-varying lot sizes. Operations Research 35 (5), 764-771.
Dolan, R.J, Simon, H., 1996. Power pricing: how managing price transforms the bottom line. New York: The Free Press.
Elmaghraby, S.E., 1978. The economic lot scheduling problem (ELSP): review and extensions. Management Science 24 (6), 587-598.
Elmaghraby, W., Keskinocak, P., 2003. Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions. Management Science 49, 1287-309.
Federgruen, A., Tzur, M., 1994. The joint replenishment problem with time-varying costs and demands: efficient, asymptotic and Є–optimal solutions. Operations Research 42 (6), 1067-1086.
Federgruen, A., Zheng, Y.S., 1992. The joint replenishment problem with general joint cost structures. Operations Research 40 (2), 384-403.
Frenk, J.B.G., Kleijn, M.J., Dekker, R., 1999. An efficient algorithm for a generalized joint replenishment problem. European Journal of Operational Research 118 (2), 413-428.
Friend, S.C., Walker, P.H., 2001. Welcome to the new world of merchandising. Harvard Business Review November, 133-41.
Fuller, J.B., O’Conor, J., Rawlinson, R., 1993. Tailored logistics: the next advantage. Harvard Business Review 71 (3), 87-98.
Ghare, P.N., Schrader, G.F., 1963. A model for exponentially decaying inventories. Journal of Industrial Engineering 15, 238-243.
Giri, B.C., Goswami, A., Chaudhuri, K.S., 1996. An EOQ model for deteriorating items with time varying demand and costs. Journal of the Operational Research Society 47, 1398-1405.
Goswami, A., Chaudhuri, K.S., 1991. An EOQ model for deteriorating items with time shortages and a linear trend in demand. Journal of the Operational Research Society 42, 1105-1110.
Goyal, S.K., 1973. Determination of economic packaging frequency for items jointly replenished. Management Science 20 (2), 232-235.
Goyal, S.K., 1974. Determination of optimum packaging frequency of items jointly replenished. Management Science 21 (4), 436-443.
Goyal, S.K., 1988a. A joint economic-lot-size model for purchaser and vendor：a comment. Decision sciences 19 (1), 236-241.
Goyal, S.K., 1988b. Economic ordering policy for jointly replenished items. International Journal of Production Research 26 (7), 1237-1240.
Goyal, S.K., 1992. An EOQ model for deteriorating items with time shortages and a linear trend in demand - a comment. Journal of the Operational Research Society 43, 931-932.
Goyal, S.K., Giri, B.C., 2001. Recent trends in modeling of deteriorating inventory: an invited review. European Journal of Operational Research 134, 1-16.
Goyal, S.K., Gupta, Y.P., 1989. Integrated inventory and models: the buyer-vendor coordination. European Journal of Operational Research 41, 261-269.
Graves, S.C., 1979. On the deterministic demand multi-product single-machine lot scheduling problem. Management Science 25 (3), 276-280.
Grznar, J., Riggle, C., 1997. An optimal algorithm for the basic period approach to the economic lot scheduling problem. Omega-International Journal of Management Science 25 (3), 355-364.
Hahm, J., Yano, C.A., 1995a. The economic lot and delivery scheduling problem: the common cycle case. IIE Transactions 27 (2), 113-125.
Hahm, J., Yano, C.A., 1995b. The economic lot and delivery scheduling problem: models for nested schedules. IIE Transactions 27 (2), 126-139.
Hahm, J., Yano, C.A., 1995c. The economic lot and delivery scheduling problem: powers of two policies. Transportation Science 29 (3), 222-241.
Hammer, M., 2001. The superefficient company. Harvard Business Review 79 (8), 82-91.
Hariga, M., 1995. An EOQ model for deteriorating items with shortages and time-varying demand. Journal of the Operational Research Society 46, 398-404.
Hariga, M., 1996. Optimal EOQ models for deteriorating items with time-varying demand. Journal of the Operational Research Society 47, 1228-1246.
Hollier, R.H., Mak, K.L., Lai, K.K., 2002. Computing optimal (s,S) policies for inventory systems with a cut-off transaction size and the option of joint replenishment. International Journal of Production Research 40 (14), 3375-3389.
Hsu, W., 1983. On the general feasibility test of scheduling lot sizes for several products on one machine. Management Science 29 (1), 93-105.
Jackson, P., Maxwell, W., Muckstadt, J., 1985. The joint replenishment problem with a power-of-two restriction. IIE Transactions 17 (1), 25-32.
Jalan, A.K., Giri, R.R., Chaudhuri, K.S., 1996. EOQ model for items with Weibull distribution deterioration, shortages and trended demand. International Journal of Systems Science 27, 851-855.
Jeuland, A.P., Shugan, S.M., 1983. Managing channel profits. Marketing Science 2 (3), 239-272.
Joneja, D., 1990. The joint replenishment problem: New heuristics and worst case performance bounds. Operations Research 38 (4), 711-723.
Jørgensen, S., Kort, P.M., 2002. Optimal pricing and inventory policies: centralized and decentralized decision making, European Journal of Operational Research 138, 578-600.
Kao, E.P.C., 1979. A multi-product dynamic lot-size model with individual and joint set-up costs. Operations Research 27 (2), 279-289.
Kaspi, M., Rosenblatt, M.J., 1985. The effectiveness of heuristic algorithms for multi-item inventory systems with joint replenishment costs. International Journal of Production Research 23 (1), 109-116.
Khouja, M., 2003. Optimizing inventory decisions in a multi-stage multi-customer supply chain. Transportation Research Part E: Logistics and Transportation Review 39 (3), 193-208.
Khoury, B.N., Abboud, N.E., Tannous, M.M., 2001. The common cycle approach to the ELSP problem with insufficient capacity. International Journal of Production Economics 73 (2), 189-199.
Lal, R., Staelin, R., 1984. An approach for developing an optimal discount pricing policy. Management Science 30 (12), 1524-1539.
Lee, F.C., Yao, M.J., 2003. A global optimum search algorithm for the joint replenishment problem under power-of-two policy. Computers and Operations Research 30 (9), 1319-1333.
Lee, H.L., 1996. Effective inventory and service management through product and process redesign. Operations Research 44 (1), 151-159.
Lee, H.L., 2000. Creating value through supply chain integration [online]. Supply Chain Management Review. Available from: http://www.manufacturing.net/scm/ [Accessed 2 March 2004].
Lee, H.L., and Whang, S., 2001. E-business and supply chain integration [online]. Stanford Global Supply Chain Management Forum. Available from: http://www.stanford.edu/group/scforum/ [Accessed 2 March 2004].
Lu, L., 1995. A one-vendor multi-buyer integrated inventory model. European Journal of Operational Research 81 (2), 312-323.
Marn MV, Rosiello RL. 1992. Managing price, gaining profits. Harvard Business Review; September-October: 84-94.
Maxwell, W.L., Muckstadt, J.A., 1985. Establishing consistent and realistic reorder intervals in production-distribution systems. Operations Research 33 (6), 1316-1341.
Mishra, A.K., 2004. Selective discount for supplier-buyer coordination using common replenishment epochs. European Journal of Operational Research 153 (3), 751-756.
Moon, I., Lee, S., 2000. The effects of inflation and time-value of money on an economic order quantity model with a random product life cycle. European Journal of Operational Research 125, 588-601.
Nahmias, S., 1982. Perishable inventory theory: a review. Operations Research 30, 680-708.
Nation Retail Security Survey 2003. Shrinking shrinkage. Security: For Buyers of Products, Systems & Services 40, 8.
Newton, F.J., 1988. Information please: do you have any information on inventory shortages? Management Accounting 70, 52-53.
Papachristos S., Skouri, K., 2003. An inventory model with deteriorating items, quantity discount, pricing and time-dependent partial backlogging, International Journal of Production Economics 83, 247-256.
Pavia, J., 2003. Just thinking. National Jeweler 97, 12.
Philip, G.C., 1974. A generalized EOQ model for items with Weibull distribution. AIIE Transactions 6, 159-162.
Rajagopalan, S., 2002. Make to order or make to stock: model and application. Management Science 48 (2), 241-256.
Rajan, A., Rakesh, Steinberg, R., 1992. Dynamic pricing and ordering decisions by a monopolist, Management Science 38, 240-262.
Sachan, R.S., 1984. On (T, Si) Policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society 35, 1013-1019.
Silver, E.A., 1976. A simple method of determining order quantities in jointly replenishments under deterministic demand. Management Science 22 (12), 1351-1361.
Spiegel, M.R., 1960. Applied differential equations. Englewood Cliffs, NJ: Prentice-Hall.
Tadikamalla, P.R., 1978. An EOQ inventory model for items with gamma distributed deterioration. AIIE Transactions 10, 78.
Teng, J.T., Yang, H.L., Ouyang, L.Y., 2003. On an EOQ model for deteriorating items with time-varying demand and partial backlogging. Journal of the Operational Research Society 54, 432-436.
van Eijs, M.J.G., 1994. Multi-item inventory systems with joint ordering and transportation decisions. International Journal of Production Economics 35, 285-292.
Viswanathan, S., Piplani, R., 2001. Coordinating supply chain inventories through common replenishment epochs. European Journal of Operational Research 129 (2), 277-286.
Wee, H.M., 1999. Deteriorating inventory model with quantity discount, pricing and partial backordering, International Journal of Production Economics 59, 511-518.
Wildeman, R.E., Frenk, J.B.G., Dekker, R., 1997. An efficient optimal solution method for the joint replenishment problem. European Journal of Operational Research 99 (2), 433-444.
Wu, K.S., 2002. EOQ inventory model for items with Weibull distribution deterioration, time-varying demand and partial backlogging. International Journal of Systems Science 33, 323-329.
Young, S.T., Nie, W.D., 1992. A cycle-count model considering inventory policy and record variance. Product and Inventory Management 33, 11-16.
Zipkin, P.H., 1991. Computing optimal lot sizes in the economic lot scheduling problem. Operations Research 39 (1), 56-63.

指導教授

陳振明(Jen-Ming Chen)

審核日期

2005-12-14

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