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

被引:13
作者
Hong, Seong Rok [1 ]
Kim, Shin Tae [1 ]
Kim, Chang Ouk [1 ]
机构
[1] Yonsei Univ, Dept Informat & Ind Engn, Seoul 120749, South Korea
关键词
RFID; supply chain control; neural network controller; amplification error function; tracking signal; INFORMATION; MANAGEMENT; SYSTEMS;
D O I
10.1080/00207540903564967
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:2613 / 2632
页数:20
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