Study on supply chain optimization scheduling of networked manufacturing

Authors:
Gu Hong;Li Chuan;Lu Zhang;Zhang Xianming
Affiliations:
Institute of Separation Machinery, Chongqing Technology and Business University, Chongqing, China;Institute of Separation Machinery, Chongqing Technology and Business University, Chongqing, China;College of Electrical and Computer Engineering, National University of Singapore, Singapore;Institute of Separation Machinery, Chongqing Technology and Business University, Chongqing, China
Venue:
ACOS'07 Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6
Year:
2007

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Dynamic scheduling for multi-site companies: a decisional approach based on reinforcement multi-agent learning

Journal of Intelligent Manufacturing

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Abstract

Supply chain scheduling is the very heartbeat of all supply chain systems. Optimization of the supply chain scheduling can help increase agility while reduce the running cost of corporations. Complying with its structure, supply chain of the networked manufacturing has the characteristics of distributed, multi plants and multi stages. In this paper, a thorough research was first done on the decision making problem of supply chain scheduling under networked manufacturing, a mathematical model was built. Based on these studies, an improved artificial fish-swarm algorithm was put forward to solve the supply chain optimization scheduling, which proposes a competition based mechanism to allocate computational resource for artificial fish with better vitality. Simulations were done to verify the algorithm, and it was proved to be very effective by artificial fish-swarm algorithm in the supply chain scheduling under networked manufacturing.