Title :
Using Artificial Neural Network in Multi-Agent Supply Chain Systems
Author :
Chen, Hsiao Ching ; Wee, Hui Ming ; Wang, Kung-Jeng ; Hsieh, Yao-Hung
Author_Institution :
Chung Yuan Christian Univ., Chungli
Abstract :
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.
Keywords :
customer satisfaction; multi-agent systems; neural nets; stock control; supply chain management; artificial neural network; customer demands; multi-agent supply chain systems; optimal inventory control; supply chain management; Artificial neural networks; Costs; Inventory control; Inventory management; Multiagent systems; Production facilities; Production systems; Robustness; Supply chain management; Supply chains; Mixed Inventory; Multi-Agent Systems; Neural Networks.; Policy; Supply Chain;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.798