Abstract: With the continuous development of automation technology and workshop intelligent technology, the integration of material equipment planning and production scheduling is getting higher and higher. Aiming at the problem of flexible job shop scheduling with AGV (automated guided vehicle), with the goal of minimizing completion time, considering the effective load time and empty time of the AGV between the loading station, machine and unloading station, a mathematical programming model is con-structed. Secondly, an effective gray wolf algorithm is proposed to solve the problem. Based on the characteristics of the problem, a three-segment code for machine selection, process sequencing and AGV handling is designed to effectively ensure that each individual can produce a feasible solution. The setting methods of key parameters a and E are improved, which effectively balances the exploration ability and local search ability of the algorithm; in order to further improve the algorithm's ability to jump out of the local optimal solution, the algorithm incorporates domain search and other methods. Finally, the case test results show that the improved gray wolf algorithm has superior performance in solving the scheduling problem of flexible job shop with AGV.

Key words: flexible job shop, AGV (automated guided vehicle) handling, grey wolf algorithm, neighborhood search