A real-time job-shop scheduling method based on adaptive agent

Authors:
Xinli Xu;Xiangli Wang;Wanliang Wang
Affiliations:
College of Information Engineering, Zhejiang University of Technology, Hangzhou, P. R. China;College of Information Engineering, Zhejiang University of Technology, Hangzhou, P. R. China;College of Information Engineering, Zhejiang University of Technology, Hangzhou, P. R. China
Venue:
ROCOM'06 Proceedings of the 6th WSEAS international conference on Robotics, control and manufacturing technology
Year:
2006

Citing 4
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Abstract

Combining the intelligent ant and reinforcement learning, an on-line job-shop scheduling model based on the adaptive agent was proposed. In the process of learning, the intelligent ant made decision according to the past rewards and an immediate reward. When the production environment changed, e.g. the machines or the orders were changed, the adaptive agent could make an adjustment and the optimal assignment of resources could be realized finally. The simulation results show that the method is effective.