Abstract
Modern manufacturing enterprises are required to negotiate with their customers and suppliers regarding to service times, prices, quality, and so on, with the objective of minimizing the inventory cost while keeping high level of service level. For maintaining a high service level, the node in the supply chain promises a guaranteed service time that when the downstream customer of this node places an order, this node should finish the production processing and deliver the order to the customer within the guaranteed service time. It is called a Guaranteed Service Model of supply chain optimization problem in existing literatures. This study aims to develop an optimization model to minimize the overall average inventory cost of the multi-stage supply chain while keeping a good customer service level, assuming that the real world supply chain can be model as a network and each node of the supply chain network follows a periodical review policy. A method of forecast based on historical customer demand data is also proposed for obtaining two critical parameters of the nodes: base stock level and average demand. Four general networks similar to realistic supply chain are tested in numerical examples, and the CPU times of this optimization model are within 1 second.