A novel Event-triggered dynamic scheduling strategy for automated guided vehicle in warehouse system

In order to improve the efficiency of warehouse system, dynamic scheduling strategies are introduced which heavily rely on the assumption that the speed of AGV is constant. This assume leads to the actual scheduling process being mismatched with the planning, then deteriorate the efficiency of scheduling strategies. An event triggered multi-task collaborative scheduling strategy for application scenarios is designed for solving this problem. Firstly, a warehouse scheduling model is proposed for multiple optimize objectives which include minimizing the total travel distance of AGVs, minimizing the penalty time for AGVs, and minimizing the range of AGVs' utilization rate. Secondly, a methodology for evaluating the inconsistency which caused by the various types of unexpected events between the offline scheduling schemes to the actual scheduling process is established. And then, the IDMOGA which integrates the event triggered strategy with DTC (Dynamic Task Chaining) scheduling is first proposed. Finally, the results of the simulation experiments show that the application of the IDMOGA has faster convergence speed, improves the cargo scheduling efficiency, significantly shortens the range of AGVs utilization rate, and is be more suitable for the application.