چكيده به لاتين
Coordinating decisions in the supply chain is a challenge for manufacturers whose goal is to optimize costs and increase supply chain profits .There are many policies to create coordination and integration in the supply chain. One of the practical policies in this field is the vendor managed inventory (VMI) policy in which retailers provide their information to the vendor and verdor manages inventories using these information. This research aims to present a new model with multivariate demand function in the field of coordination using VMI policy, whose demand depends on price and shelf space. The important point is that in this model, both the brand and advertising effects have been considered and also the optimal pricing has been adjusted. The general research method to answer the questions that will be asked in the research, is based on mathematical modeling and numerical analysis. In this regard, we analyze two types of supply chains. The first supply chain consists of one manufacturer and one retailer, and the second supply chain consists of one manufacturer and two retailers. By designing revenue sharing contracts and using VMI policies, system performance was improved. In fact, no VMI policy was considered in the first model and instead, VMI policy was implemented in the second model. The results showed that by designing the revenue sharing contract and using VMI policy, the performance of the system was improved and led to increased profitability for both sides of the supply chain as well as the profitability of the whole chain. The developed models have been solved using Mathematica software and the optimal values of retail price, shelf space and wholesale price have been determined. Also, the application of the model in the real world and the developed solution method are shown by numerical examples. In the numerical examples, it was observed that the price of products in the centralized and coordinated model decreases compared to the decentralized model, which increases the profitability of the supply chain. Finally, sensitivity analysis was performed on some parameters affecting the model and the results showed that the model is more sensitive to the price elasticity parameter on demand and which mean that this paramenter should be more considered in real-world.
