Centralized Scheduling of Service Vehicles for Aircraft Turnaround Based on Partheno-Genetic Algorithm

In order to solve the centralized scheduling problem of service vehicles for aircraft turnaround, a partheno-genetic algorithm with hierarchical encoding structure was proposed. The service activity number and vehicle number were employed to encode the control and parametric genes chromosome, respectively, which characterized the temporal and vehicle scheduling rules in turnaround service, ensuring the applicability of algorithm. The crossover and mutation operators were designed, which acted on each control genes chromosome segment and between different parametric genes chromosome segments. The schedulable capacity concept for service vehicle was introduced in chromosome decoding process to optimize search ability of algorithm. The fitness function was established to minimize the penalty of flight delay due to turnaround service and driving distance cost of vehicle, which measured the overall efficiency of turnaround service and vehicle scheduling. The data of aircraft turnaround was used to validate the proposed algorithm, and also the nearest vehicle scheduling strategy and workload balance scheduling strategy were compared. The results indicate that, the convergence of the proposed algorithm is acceptable, and flight delays in these two scheduling strategies are close, while the vehicle driving time is 40% shorter in the nearest vehicle scheduling strategy.