Supplychain Inventory Policy Using Intelligent Agents and Artificial Neural Network

In current global competitive market, manufacturers must set up an efficient supply chain and network to cut cost. Each company aims to supply the right quantity of products to customer in right place and at right time with right cost. Each supplier must respond to the short life-cycle and quick response need for the terminal products. To satisfy the varying customer demand is one of the most important issues of the supply chain management, and enterprises should enhance the long-term advantage through the optimal inventory policy. We construct the supply chain framework with mixed inventory policies of facilities to consider the impact factors of the total supply chain cost. This paper develops an intelligent agents system to simulate supply chain system. Artificial Neural Network is used to derive the optimal inventory policies. We try to realize the performance of the optimal inventory policies by cutting costs and increase running efficiency. The mixed inventory policy and ANNs(Artificial Neural Network) results provide managerial insights on the impact of the decision making in factory, wholesaler, distributor and retailer.