Title :
Applying Adaptive Multi-Agent Modeling in Agile Supply Chain Simulation
Author :
Li, Yan ; Zhao, Jian-min
Author_Institution :
Dept. of Comput. Sci. & Technol., Weifang Univ.
Abstract :
An agile supply chain focuses on responding to unpredictable market changes and capitalizing on them through fast delivery and lead-time flexibility. It deploys new technologies, methods, tools, and techniques to solve unexpected problems. Recently, multi-agent technology is increasingly regarded as a good solution for supply chain management. This paper attempts to apply adaptive multi-agent modeling method to agile supply chain simulation, and illustrates the concrete modeling process with task allocation problem. A two-leveled reinforcement learning mechanism to improve the model is designed, and some related topics are also discussed in this paper
Keywords :
digital simulation; learning (artificial intelligence); multi-agent systems; supply chain management; adaptive multiagent modeling; agile supply chain simulation; concrete modeling process; task allocation problem; two-leveled reinforcement learning mechanism; unpredictable market changes; Collaboration; Collaborative work; Computational modeling; Computer science; Computer simulation; Cybernetics; Globalization; Learning; Machine learning; Multiagent systems; Supply chain management; Supply chains; Agile supply chain; adaptive multi-agent modeling; agent technology;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258941
