臺灣博碩士論文加值系統

傳統的存貨規劃多以買方為出發點，決定其最適訂購量，模型中基本假設太多，使得其實用性大為降低。換個角度以賣方為出發點，則強調可提升其利潤之定價與補貨政策。許多學者已開始注重整合性的存貨管理，亦即以買賣雙方為一系統的觀點發展可降低雙方聯合成本，或提高彼此利潤的整合性存貨政策。
一般而言，買賣雙方的存貨系統可視為簡單的兩人賽局。大多數的存貨模型將買賣雙方的問題分開處理，即使是整合性存貨管理的聯合經濟批量(Joint Economic Lot Size；JELS)模型，亦未考量彼此的競爭情況。將賽局引入買賣雙方的存貨模型時，決策者面臨的難題不僅是如何建立存貨問題的賽局模式，還須致力於參賽者相關均衡決策的最佳化問題。近年來已有學者應用基因演算法與其他計算智慧(Computational Intelligence)的方法來求取賽局的均衡解。
本研究在建立買賣雙方的Stackelberg存貨賽局後，以微粒群演算法並結合共生機制(Symbiosis Phenomenon)的限制式處理技術來求解對應之非線性最佳化問題(Constrained Nonlinear Optimization Problem; CNOP)。共生機制下的微粒群兼容可行與不可行粒子，迭代過程中使得不可行的個體，逐漸成為可行的個體或是更接近可行域；可行的粒子則朝著均衡方向飛行，以決定買賣雙方的定價與缺/補貨策略。

One of the best known problems which inventory models address is the ordering quantity problem for the buyers Traditional economic order quantity (EOQ) model and its variants lie in this category. On the opposite side, which means from the seller’s point of view, a lot of work focus on the issue of developing a pricing and replenishment scheme for the seller to minimize his total cost. The models built from the seller’s view are appropriate when a price discount is the instrument for the seller to influence buyer’s behavior in a form of compensation. No matter what view you prefer, models unilaterally built from one perspective, either buyer or seller’s view, might lead to myopic decisions. Hence, the integrated inventory control models discussing the joint optimal decisions of the seller and the buyer have been received significant attention. Above JELS models are suitable for the situation when both the seller and the buyer belong to the same organization.
Although the two approaches described in the last two paragraphs are appealing, a seller-buyer inventory control problem is basically a two-person game in which both players try to maximize (or minimize) their individual gains (or costs). Analyzing the problem from buyer or seller’s perspective cannot adequately describe a competitive situation, neither could the JELS models. So, game theory, a mathematical theory dealing with decision making among multiple agents may be a more desirable approach for seller-buyer inventory systems.
The challenges the decision makers confront are not only modeling the game, but also the effort devoted to optimize relevant decisions for both players. After modeling the inventory system as a Stackelberg game between the seller and the buyer, particle swarm optimization (PSO) algorithm combined with constrains handling technique based on symbiosis phenomenon in mature, are used to solve this constrained nonlinear optimization problem (CNOP). Symbiosis mechanism, which incorporates infeasible solutions into the population, makes PSO capable to obtain better exploration in the search space and, finally, finds the equilibrium result that delineates the pricing, ordering, and backordering sizes decisions for the seller and buyer.

摘要 I
Abstract II
目錄 IV
圖目錄 VI
表目錄 VII
第一章　緒　論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究方法及架構 2
第二章　文獻探討 5
2.1賽局理論 5
2.1.1賽局理論之簡介 5
2.2買賣雙方的存貨系統 6
2.3賽局均衡解的求算方法 12
2.4微粒群演算法與最佳化問題 14
2.4.1微粒群演算法簡介 14
2.4.2最佳化問題 16
第三章　缺貨後補之存貨賽局模型 21
3.1基本假設 21
3.2符號說明 22
3.3缺貨後補的非合作賽局模型 22
3.4微粒群求解演算法 28
第四章　範例驗證 34
4.1求解Chiang et al.的賽局模型 36
4.2求解缺貨後補的存貨賽局模型 41
4.3慣性權重的分析比較 43
第五章　結論與未來研究方向 45
5.1研究結論 45
5.2未來研究方向 46
參考文獻 47

[1]江明倫，「應用Stackelberg策略於單一商品供應鏈存貨模式之探討」，南台科技大學工業管理研究所，2004。
[2]胡曉輝，「粒子優化算法介紹」，http://web.ics.purdue.edu/~hux/tutorials.shtml，2002。
[3]張維迎，「賽局理論與信息經濟學」，台北，茂昌圖書有限公司，1999。
[4]廖慶榮，「作業研究」，台北，華泰文化有限公司，2005。
[5]謝淑貞，「賽局理論」，台北，雙葉書廊有限公司，1995。
[6]Alemdar, N.M. and Sirakaya, S., “On-line Computation of Stackelberg Equilibria with Synchronous Parallel Genetic Algorithms,” Journal of Economic Dynamics and Control, Vol.27, 2003, pp.1503-1515.
[7]Banerjee, A., “On ‘A quantity discount pricing model to increase vendor’s profit’”, Management Science, Vol.32, 1986a, pp.1513-1517.
[8]Banerjee, A., “A joint economic lot size model for purchaser and vendor”, Decision Science, Vol.17, 1986b, pp.292-311.
[9]Boeringer, D. W. and Werner, D. H., ：Particle Swarm Optimization Versus Genetic Algorithms for Phased Array Synthesis,“ IEEE Transactions on Antennas and Propagation, vol. 52, no. 3, 2004, pp. 771-778.
[10]Chiang, W.C., Fitzsimmons, J. Huang, Z. and Li S., “A Game-Theoretic Approach to Quantity Discount Problems,” Decision Sciences, 1994, pp.153-168.
[11]Chunlin, J.I., “A Revised Particle Swarm Optimization Approach for Multi-objective and Multi-constraint Optimization,” Proc. GECCO 2004 Conference, 2004.
[12]Dada, M. and Srikanth, K.N., “Pricing policies for quantity discounts,” Management Science, Vol.33, No.10, 1987, pp.1247-1252.
[13]Dong, Y., Tang, J.F., Xu B.D. and Wang D.W., “An Application of Swarm Optimization to Nonlinear Programming,” Computers and Mathematics whit Applications, Vol.49, 2005, pp.1655-1668.
[14]Eberhart, R.C. and Kennedy, J., “Particle swarm optimization,” Proceedings of IEEE International Conference on Neural Networks, IV, 1995, pp.1942-1948.
[15]Goyal, S.K., “An Integrated Inventory Model for a Single Supplier-Single Customer Problem,” International Journal of Production Research, Vol.15, 1976, pp.107-111.
[16]Goyal, S.K., “A joint economic-lot-size model for purchaser and vendor: A comment,” Decision Science, Vol.19, 1988, pp.236-241.
[17]Goyal, S.K. and Gupta, Y.P., “Integrated inventory models: The buyer-vendor coordination,” European Journal of Operational Research, Vol.41, 1989, pp.261-269,
[18]Koller, D. and Megiddo, N., “Efficient Computation of Equilibria for Extensive Two-Person Games,” Games and Economic Behavior, Vol.14 1995, pp.247-259
[19]Kohli, R. and Park, H., “A Cooperative Game Theory Model of Quantity Discounts,” Management Science, Vol. 35, 1989, pp. 693-707.
[20]Lal, R. and Staelin, R., “An Approach for Developing an Optimal Discount Pricing Policy,” Management Science, Vol.30, No.12, 1984, pp.1524-1539.
[21]Lee, H.L. and Rosenblatt, M.J., “A Generalized Quantity Discount Pricing Model to Increase Supplier’s Profits,” Management Science, Vol.32, No.9, 1986, pp.1177-1185.
[22]Li, S.X., Huang, Z. and Ashley, A., “Seller-Buyer System Cooperation in a Monopolistic Market,” Journal of the Operational Research Society, Vol.46, No.12, 1995, pp.1456-1470.
[23]Li, S.X. and Huang, Z., “Improving buyer-seller system cooperation through inventory control,” International Journal of Production Economics, Vol.43, 1996, pp.37-46.
[24]Lu, L., “A One-vendor multi-buyer integrated inventory model,” European Journal of Operational Research, Vol.81, 1995, pp.312-323.
[25]Monahan, J.P., “A quantity discount pricing model to increase vendor profits,” Management Science, Vol.30, No.6, 1984, pp.720-726.
[26]Parlar, M. “Game Theoretic Analysis of the Substitutable Product Inventory Problem with Random Demands,” Naval Research Logistics, Vol.35, 1988, pp.397-409.
[27]Parlar, M. and Wang, Q., “Discounting Decision in a Supplier-Buyer Relationship with a Linear Buyer’s Demand,” IIE Transaction, Vol.26, No.2, 1994, pp.34-41.
[28]Pavlidis, N.G., Parsopoulos, K.E. and Vrahatis, M.N., “Computing Nash equilibria through computational intelligence methods,” Journal of Computational and Applied Mathematics, Vol.175, 2005, pp.113-136.
[29]Rosenblatt, M.J. and Lee, H.L., “Improving profitability with quantity discounts under fixed demand,” IIE Transactions, Vol.17, No.4, 1985, pp.388-395.
[30]Shi, Y.H. and Eberhart, R.C., “A modified particle swarm optimizer,”In IEEE World Congress on Computational Intelligence, IEEE Press, 1998a.
[31]Shi, Y.H. and Eberhart, R.C., “Parameter selection in particle swarm optimization,” In Evolutionary Programming VII (Berlin, 1998), pp. 591–600, 1998b.
[32]Silver, E.A., Pyke, D.F. and Peterson, R., “Inventory Management and Production Planning and Scheduling,“ 3rd Edition, John Wiley & Sons, New York, 1998.
[33]Sucky, E. “A single buyer-single supplier bargaining problem with asymmetric information - theoretical approach and software implementation,” Proceedings of the 36th Hawaii International Conference on System Sciences, 2003.
[34]Vallee, T. and Basar, T., “Off-Line Computation of Stackelberg Solutions with the Genetic Algorithm,” Computational Economics, Vol.13, 1999, pp.201-209.
[35]Wang, Q. and Parlar, M., “Static game theory models and their applications in management science,” European Journal of Operational Research, Vol.42, 1989, pp.1-21.
[36]Wang, Q. and Parlar, M., “A three-person game theory model arising in stochastic inventory control theory,” European Journal of Operational Research, Vol.76, No.1, 1994, pp.83-97.
[37]Weng, Z. K., “Modeling quantity discount under general price sensitive demand functions: optimal policies and relations,” European Journal of Operational Research, Vol.86, 1995, pp.300–314.
[38]Von Neumann, J. and Morgenstern, O., "The Theory of games and economic behavior," Princeton University Press, 1944.
[39]Xing, W. and Wu, F.F., “A game-theoretical model of private power production,” International Journal of Electrical Power and Energy Systems, Vol.23, 2001, pp. 213-218.
[40]Yang, P. and Wee, H., “Economic ordering policy of deteriorated item for vendor and buyer: an integrated approach,” Production Planning and Control, Vol.11, 2000, pp.474–480.
[41]Yang, P.C., “Pricing strategy for deteriorating items using quantity discount when demand is price sensitive,” European Journal of Operational Research, Vol.157, 2004, pp.389-397.
[42]Zhenya, H., Chengjian, W., Luxi, Y., Xiqi, G., Susu, Y., Eberhart, R.C. and Shi, Y., “Extracting rules from fuzzy neural networks by particle swarm optimization,” IEEE International Conference on Evolutionary Computation, Vol.1, 1998, pp.74-77.