关键词: 柔性作业车间, 自动导向车, 集成调度, 预维护, 混合文化基因算法

Abstract: Aiming at the integrated scheduling problem of production and logistics in flexible job shops with multi-AGVs,the preventive maintenance plans of machines were considered. A mathematical model was established with the objective of minimizing the makespan,and a hybrid memetic algorithm integrating multiple population initialization strategies and various neighborhood search strategies was designed to solve it. The algorithm adopted a two-layer encoding method based on operations and machines,and heuristic rules were used to schedule AGVs during the decoding process. Two decoding methods were designed respectively for the preventive maintenance strategy of first PM then sheduling and age-based preventive maintenance strategy. Finally,two groups of experiments were designed. In the first group,benchmark instances were solved,and the results were compared with those of multiple algorithms to demonstrate the effectiveness of the proposed algorithm. In the second group of experiments,the performance of the proposed algorithm was compared under different preventive maintenance strategies. The results show that the scheduling scheme using age-based preventive maintenance strategy significantly reduced the makespan,and the extension of processing time due to machine preventive maintenance is less pronounced when this strategy is employed. In summary,the algorithm and preventive maintenance strategy proposed demonstrate excellent performance in addressing this problem.

Key words: flexible job shop, AGV, integrated scheduling, preventive maintenance, hybrid memetic algorithm