Dynamic Scheduling for Airport Special Vehicles Based on a Multi-strategy Hybrid Algorithm

When arriving at the airport, flight needs to be served by special vehicles. Aiming at the dynamic time window scheduling problem of airport refueling vehicles, this paper establishes a vehicle routing problem model with time window to minimize the operating cost. Firstly, a multi-strategy genetic algorithm is designed to gain the solve time window scheduling problem, which employs the crossover based on particle swarm optimization to accelerate the early search capability, and the local search method based on simulated annealing to increase the local optimization ability. Then aiming at dynamically adjusting vehicle routes on the basis of static scheduling, a local replanning strategy based on a dynamic time window is introduced, which uses the original route matching and rescheduling strategy. Experimental results show that the multi-strategy hybrid algorithm can effectively reduce the number of routes and vehicles the airport needed. Under different scales' dynamic changes of time windows, the algorithm could enable vehicles to still meet time constraints and effectively minimize the change of routes.