Using artificial neural network in multi-agent supply chain systems

被引:0
|
作者
Chen, Hsiao Ching [1 ]
Wee, Hui Ming [1 ]
Wang, Kung-Jeng [2 ]
Hsieh, Yao-Hung [1 ]
机构
[1] Chung Yuan Christian Univ, Dept Ind Engn, Chungli 32023, Taiwan
[2] Natl Taiwan Univ Sci & Technol, Dept Ind Management, Tokyo 106, Japan
关键词
multi-agent systems; mixed inventory policy; supply chain; neural networks;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In modern global market, one of the most important issues of the supply chain (SC) management is to satisfy changing customer demands, and enterprises should enhance the long-term advantage through the optimal inventory control. In this study, we model a supply chain framework by multi-agent with mixed inventory policies of facilities to consider the impact factors of the total supply chain cost. This paper develops a multi-agent system to simulate supply chain system. Artificial Neural Network (ANN) is used to derive the optimal inventory policies in the SC numbers. We examine the performance of the optimal inventory policies by cutting costs and increasing supply chain management efficiency. The proposed inventory policy using multi-agent and ANN provides managerial insights on the impact of the decision making in all the SC numbers.
引用
收藏
页码:348 / +
页数:2
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