Neural network controller with on-line inventory feedback data in RFID-enabled supply chain

Abstract

The item-level visibility which can be secured by RFID technology can help the inventory records of a supply chain correspond closer to the actual inventories. More accurate and timely tracking of chain-wide inventories provides a great potential for optimised on-line control of supply chains. In this paper, we develop an on-line neural network controller that optimises a three-stage supply chain. With the inventory data feedback from an RFID system, the neural network controller minimises the total cost of the supply chain rapidly while satisfying a target order fulfilment ratio. As a test bed of the neural network controller, we develop the beer game model of the supply chain. We demonstrate through simulation-based experiments that the neural network controller shows the highest performance when the inventory data is secured from item-level RFID data.