The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was established and based on relevant analysis,the original model could be transformed by minimax method.Then,the optimal order quantity and production quantity influenced by service level constraint were analyzed and the boundary of optimal order quantity and production quantity was given.According to this boundary,the effective method and tactics were put forward to solve the transformed model.In case analysis,the optimal expected total cost of two-echelon inventory can be obtained and it was analyzed how service level constraint and safety factor influence the optimal expected total cost of two-echelon inventory.The results show that the optimal expected total cost of two-echelon inventory is constrained by the higher constraint between service level constraint and safety factor.
A replenishment decision-making model for supply-hub is firstly established from the angle of supplier, and optimal replenishment decision of the supplier is analyzed. Then, inventory optimization model for supply-hub is formulated from the angle of the manufacturer, and the optimization algorithm for obtaining optimal inventory levels is given. The result shows that liability period decides the share of the inventory cost between two sides in supply chain. With the increase of liability period, the service level has been quickly reduced even though the manufacturer's cost has been cut down by transferring the inventory cost to the supplier. As to the safety inventory, if the lower bound of components safety inventory increases, the supplier's cost will rise up more slowly than the liability period does, while the service levels increases as the safety inventory's lower bound is raised.
The existing research of supply coordination under uncertain delivery time mainly focuses on the collaboration between the supplier and the manufacturer, which aim at minimizing the total cost of each side and finding comparative optimal solutions under decentralized decision. In the supply coordination, the collaboration between suppliers in assembly system is usually not considered. As a result, the manufacturer's production is often delayed due to mismatching delivery of components between suppliers. Therefore, to ensure supply coordination in assembly system, collaboration between suppliers should be taken into consideration. In this paper, an assembly system with two suppliers and one manufacturer under uncertain delivery time is considered. The model is established and optimal solution is given under decentralized decision. Furthermore, the cost functions of two suppliers are both convex, and a unique Nash equilibrium exists between two suppliers. Then the optimal decision under supply coordination is analyzed, which is regarded as a benchmark for supply coordination. Additionally, the total cost of the assembly system is jointly convex in agreed delivery time. To achieve supply coordination a bonus policy is explored in the assembly system under uncertain delivery time, and the total cost under bonus policy must be lower than under decentralized decision. Finally the numerical and sensitivity analysis shows the cost of assembly system under bonus policy equals that under supply coordination, and the cost of each side in assembly system under bonus policy is lower compared to that under decentralized decision. The proposed research minimizes the total cost of each side with bonus policy in assembly system, ensures the supply coordination between suppliers and the manufacturer, and improves the competiveness of the whole supply chain.
