نوع مقاله : پژوهشی
1 گروه مهندسی صنایع، دانشگاه الزهرا
2 دانشکدهی مهندسی صنایع، دانشگاه خواجه نصیرالدین طوسی
3 گروه مهندسی صنایع، دانشگاه الزهرا(س)
عنوان مقاله [English]
Organizations in a supply chain are independent entities. Although a completely integrated solution may result in optimal system performance, supply chain members are interested in optimizing their own objective rather than that of the entire system. Thus, a key point in supply chain management is to develop mechanisms that can coordinate independent member decisions in order to optimize system performance. Vendor-managed inventory (VMI) is a new method in supply chain integration, in which the supplier is responsible for the retailers inventory replenishment and control. One of the most important tools for building an integrated supply chain is pricing, which increases the benefits of a supply chain through a better matching of supply and demand. Moreover, the demand rate of most items is price-dependent, and downstream members order to upstream members based on their demand. So, its necessary to consider the pricing problem besides inventory problems. In this article, the inventory model for two echelon single manufacturer-single retailer decentralized supply chain under the VMI policy is considered. This model is formulated with the aim of optimizing the replenishment frequency, replenishment quantity and pricing policies at the same time in order to maximizing supply chain profit. The demand is price sensitive, and the manufacturer, in order to meet the demand, sends the production lot to the retailer in several smaller lots. Producing defective items is an inevitable issue that the companies face during the production process, which happens when the system is out of control. In this model, the production process is imperfect and shortage is allowed. Game theory has become an essential tool in the analysis of supply chains with multiple agents, often with conflicting objectives. Often, analysis of a non-coordination situation is performed using the Stackelberg game. We present a simple algorithm and program to find the Stackelberg game equilibrium. Next, we solve a numerical example to illustrate the solution procedure, the algorithm and program. Finally, the effects of relevant parameters on chain member profits and optimal decision values are proposed by sensitivity analysis.