恶劣天气下进场航班运行韧性评估与提升方法OA

To address the problem of approach flight delays and reduced operational efficiency caused by severe weather,a quantitative assessment framework for operational resilience in arrival operations is developed.A Greedy Algorithm(GA)embedded within a Receding Horizon Control(RHC)frame-work is proposed to optimize the sequencing of weather-affected approach flights,enabling rapid im-provement of key performance indicators during the resilience recovery phase and enhancing overall op-erational resilience.First,based on the dynamic evolution pattern of arrival flight performance,com-prising four stages:stable,disrupted,recovery,and new stable,delay duration,on-time perfor-mance,and landing throughput under severe weather conditions are selected as fundamental indica-tors.Incorporating actual operational characteristics,a comprehensive resilience metric is constructed that integrates system redundancy and average recovery performance compensation.Second,an air-borne holding cost function is formulated based on aircraft type and delay duration,balancing eco-nomic efficiency and fairness principles.Third,the RHC+GA approach decomposes the dynamic opti-mization problem through a rolling time-domain mechanism.Aiming to minimize flight airborne hold-ing costs,the greedy algorithm yields locally optimal solutions and thereby generates an improved flight sequence under adverse weather conditions.Finally,using a thunderstorm scenario at Tianjin Binhai International Airport for verification.Results show that under the actual scheduling sequence,the operational resilience of arriving flights is 1.529.After reordering with the RHC+GA method,re-silience increases to 2.791,an 82.5%improvement,while the average delay per aircraft is reduced by 6 minutes,significantly accelerating operational performance recovery.