Research On Collaborative And Dynamic Scheduling Of Ground Support Vehicles For Large Airports

With the rapid development of the civil aviation transportation industry,the number of takeoffs and landings of airport flights and passengers’ throughput is constantly increasing.The contradiction between the increasing number of flights and the airport’s limited resources has gradually become prominent.How to ensure the regular operation of all flights has become a vital issue.Ground support services are an essential part of ensuring the regular operation of flights.Various service vehicles in the airport are mainly dispatched separately by different units or ground service companies,and dispatching plans are designed based on manual experience.It is challenging to ensure optimal dispatching results.When vehicle resources are tight,human experience may not be able to get a feasible solution,so that causes flight delays and other situations.Therefore,to ensure the normal operation of flights,it regular great significance to study airport support vehicles’ scheduling.To solve the scheduling problem of large airport ground support vehicles.First,analyze the flight guarantee process,taking the service process of ferry buses,mobile aircraft landing stairs,and refueling vehicles as examples.According to the constraints and different requirements in the actual dispatch of airport support vehicles,a vehicle coordinated dispatch model and vehicle dynamic dispatch are established.In the coordinated vehicle scheduling problem,a model with the smallest total travel time of all vehicles and the highest degree of total equilibrium as the goal and a multi-objective optimal scheduling model considering the differences between different vehicle types are established from a global perspective.In the vehicle dynamic scheduling problem,a dynamic scheduling model with the goal of minimizing the total travel time of different vehicles is established for the change of information.Secondly,the NSGA-II and NSGA-III algorithm frameworks are used to solve the problem of coordinated vehicle scheduling.The CSP idea is used to generate initial feasible solutions,and the corresponding cross-mutation operator is designed to improve the algorithm’s efficiency.A vehicle coordinated scheduling algorithm is proposed.Different scheduling strategies are adopted for dynamic scheduling problems according to additional information changes,including global re-adjustment,changed partial readjustment,and local re-adjustment strategies.The regional re-adjustment strategy mainly uses an improved discrete differential evolution algorithm as the primary solution algorithm.Finally,mine the vehicles’ actual operating data at Kunming Changshui International Airport to obtain information such as the travel time between different stops.The flight data and vehicle data are input into the model.The experimental results show that the vehicle collaborative scheduling algorithm has more significant advantages in travel time and task balance than manual scheduling strategies.The experimental results show that the dynamic vehicle scheduling algorithm can well inherit the coordinated vehicle scheduling scheme when considering the influence of flight information changes,meeting the requirements of vehicle dynamic scheduling,and reducing vehicle operating costs.