Airport schedule allocation based on flight revenue maximization
Airport flight schedules optimization is a critical strategy for improving airport operational efficiency.In view of the problem that existing research has predominantly focused on the allocation of arrival and departure flight slots,emphasizing congestion equilibrium and fairness in distribution,but seldom consider the factor of the aspect of flight schedule revenue,a multi-objective flight schedule optimization model was proposed,which maximizing operational revenue for airlines while minimizing the overall flight schedule deviation and fairness deviation.An enhanced particle swarm algorithm was applied to solve the proposed model,and its effectiveness was validated using histori-cal data from Shenzhen Bao'an Airport.Test results show that after optimization,the average reve-nue for airlines has increased by 0.231％,the average fairness deviation coefficient has decreased by 35.455％,and the average schedule adjustment has reduced by 11.243％.These results demon-strate the efficacy of the approach in enhancing airline revenue.
air traffic flow managementPareto solutionmulti-objective algorithmflight schedule optimization
NETL
NSTL
万方数据
