Hybrid scheduling method for automatic guided vehicles in intelligent warehouses considering power management

Predictive management of power consumption during static scheduling of outfitting automatic transportation equipment is very difficult. In addition, dynamic scheduling has poor response ability to sudden failures and emergency order insertion. To solve this problem, this paper proposes a scheduling approach for AGVs (automatic guided vehicles) in intelligent outfitting warehouses based on periodic driving and event triggering and integrating electricity power management. First, a power consumption model for AGVs is established and used to calculate the charging time of AGVs in initial scheduling. The charging time can be preplanned to avoid disturbance to the scheduling process. Second, considering the dynamic nature of transportation tasks, a periodically driven scheduling method is established to cope with uncertain emergency transportation tasks. In addition, considering the issue of sudden AGV failures, an event-triggered strategy is established to reduce the impact of sudden AGV failures on the scheduling process. Finally, an optimization algorithm based on power consumption and failure maintenance for outfitting vehicle scheduling is developed to solve the optimization model in a specific case. The proposed method can preplan the charging time according to the vehicle power consumption. Rescheduling is carried out for sudden failure and emergency tasks to improve the dynamic response capability of outfitting transport vehicles.