关键词: 航空运输, 机场中断恢复, 双层规划模型, 旅客取消, 航班结构调整

Abstract: Extreme weather events and other emergencies may disrupt airport operations. The conventional recovery strategies typically resume flight schedules through time extension after disruptions, but often overlook passenger cancellations caused by prolonged delays and the flexibility of transport capacity structures. To address this, this study develops a dual-layer optimization model for departure recovery that incorporates both passenger cancellations and flight structure adjustments. The upper layer optimizes capacity allocation through structural strategies such as flight consolidation, aircraft swaps, and standby replacement to minimize operational costs. The lower layer optimizes departure times under constraints like capacity limits, balancing cancellations with total delay duration. Using the Weibull distribution to characterize cancellation probabilities under delays, the model introduces flight duration and high-speed rail accessibility parameters to reflect flight heterogeneity. A co-evolutionary algorithm integrating simulated annealing, constraint methods, and non-dominated sorting is designed to solve the model. The validation was performed using Kunming Changshui International Airport as an example, and the result demonstrates that compared to baseline recovery plans based on time extension and departure scheduling optimized solely for takeoff times, the proposed method reduced total operational costs by 37.27% and 11.51%. Cancellations decreased by 42.08% and 13.50%, and total delay duration is reduced by 36.46% and 11.21%. With consideration of passenger behavior responses and departure decisions, this study provides actionable decision-making for coordinated recovery during large-scale operational disruptions at airports.

Key words: air transportation, airport disruption recovery, bi-level programming model, passenger cancellations, flight structure adjustment