Abstract
Considering the complexity of flexible workshop scheduling, combined with plant production process characteristics and constraints, we constructed a multi-agent system model to solve multi-objective flexible workshop scheduling problems. This paper proposed an algorithm which was a combination of the ant colony algorithm and Q-learning algorithm. This paper also analyzed and implemented how to solve the workshop scheduling optimization problem. Finally, this paper proved the validity of methods to solve the multi-objective flexible workshop scheduling optimization problems with examples on JADE platform.
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