عنوان مقاله [English]
The goal of supply chain management is to enhance various functions of different parts and levels of a supply chain to obtain the maximum possible profit. But this goal is not completely achievable due to the fact that there are differences between mentioned parts and levels, in their attitude towards the goals. These differences, for example pricing, stocking, and the costs related to parts and levels, will gradually result in a deduction in strength and competitiveness in system. In this study, multi-echelon supply chain has been investigated using game theory approach and considering the dependence of demand to selling price, fuzzy marketing costs, and discounts for all units. The problem has been modeled assuming that there’s no cooperation between different levels. Also, Stackelberg model assumptions have been taken into account, in which each level, with respect to market conditions, can undertake the leadership task. The aim of this problem is to determine the best decision of each player to obtain the optimal order quantity, a shortage for manufacturer and the selling price of each player, and to maximize incomes, to minimize costs and in general, to maximize possible profit for all players participating in the chain. GAMS softwares and metaheuristic algorithms have been used to solve the problem. Finally, the profit for supply chain members’ in different leadership conditions have been analyzed by generating different examples.
 Amoozad Mahdiraji, H., Jaafarnejad, A., Moddares Yazdi, M., & Mohaghar, A. (2014). Cooperation modeling for unlimited three echelon supply chain: Game theory approach, Management Research in Iran, 18(1), 171-191. (in Persian).
 Akbarfakhrabadi, H.R., Gheidar-Kheljani, J., & Ghodsypour, S.H. (2016). Competition modeling in coordinating a three level supply chain, Modern Research in Decision Making, 1(3), 1-22. (in Persian).
 Notash, M., Zandieh, M., & Dorri Nokorani, B. (2015). Using a genetic algorithm approach for designing multi-objective supply chain network, Management Research in Iran, 18(4), 183-203. (in Persian).
 Cai, G. G., Chiang, W. C., & Chen, X. (2011).Game theoretic pricing and ordering decisions with partial lost sales in two-stage supply chains.International Journal of Production Economics, 130(2), 175-185.
 Aust, G., & Buscher, U. (2012). Vertical cooperative advertising and pricing decisions in a manufacturer–retailer supply chain: A game-theoretic approach.European Journal of Operational Research, 223(2), 473-482.
 Zhao, J., & Wei, J. (2014). The coordinating contracts for a fuzzy supply chain with effort and price dependent demand. Applied Mathematical Modelling,38, 2476-2489.
 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.
 Jaber, M. Y., Osman, I. H., & Guiffrida, A. L. (2006). Coordinating a three-level supply chain with price discounts, price dependent demand, and profit sharing.International Journal of Integrated Supply Management, 2(1), 28-48.
 Jaber, M. Y., & Goyal, S. K. (2008). Coordinating a three-level supply chain with multiple suppliers, a vendor and multiple buyers. International Journal of Production Economics, 116(1), 95-103.
 Yu, Y., & Huang, G. Q. (2010). Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family. European Journal of Operational Research, 206, 361-373.
 Huang, Y., Huang, G. Q., & Newman, S. T. (2011). Coordinating pricing and inventory decisions in a multi-level supply chain: A game-theoretic approach.Transportation Research Part E: Logistics and Transportation Review, 47(2), 115-129.
 Sinha, A., Malo, P., Frantsev, A., & Deb, K. (2014). Finding optimal strategies in a multi-period multi-leader–follower Stackelberg game using an evolutionary algorithm. Computers & Operations Research, 41, 374-385.
 Esmaeili, M., Aryanezhad, M. B., & Zeephongsekul, P. (2009)49. A game theory approach in seller–buyer supply chain. European Journal of Operational Research, 195(2), 442-448.