Dynamic Scheduling of Multi-agent Electromechanical Production Line based on Biological Iterative Algorithm

Abstract

In order to solve the dynamic job scheduling problem in current intelligent machining systems, the author proposes a multi-agent electromechanical production line dynamic scheduling based on iterative algorithms. The author designed a collaborative control method for hybrid micro assembly production lines based on multi-agent technology. Firstly, a mathematical model is used to describe the collaborative control objectives of the production line, and a hybrid micro assembly production line information collection and integration framework is constructed to obtain production line information. By combining the dynamic coordination performance of multi-agent technology, a collaborative control model for production lines is constructed, with the goal of minimizing processing costs as the collaborative control objective. The optimal collaborative control scheme is solved to achieve collaborative control of hybrid micro assembly production lines. The experimental results show that compared with traditional methods, the collaborative control task allocation time obtained by applying this method is shorter, with a minimum value of 15.38 seconds, indicating that this method has higher efficiency in collaborative control of production lines. Compared with traditional methods, the collaborative control task allocation time after applying this method is shorter, effectively reducing the production line processing cost, proving the feasibility of this method.