Research on Irregular Flight Recovery Strategy Under Different Flight Route Types With Big Data Computing

During periods of extreme weather conditions, airport closures, or other unforeseen circumstances, air-lines frequently encounter disruptions in their flight schedules, posing flight recovery as a recurrent operational challenge. This paper aims to explore the impact of passenger transfer costs on flight recovery across various route types. Drawing on established methods used to calculate aircraft maintenance and crew assignment costs, this study utilizes an improved large-scale neighborhood search algorithm to perform a large number of calculations on a realistic dataset of airlines, meticulously analyzes the amalgamation of passenger transfer costs across different route types and proposes tailored strategies to mitigate disruptions. Through simulation experiments, the research evaluates the influence of various passenger transfer methods on flight recovery across diverse route types, with the goal of furnishing airlines with more adaptable and targeted decision support.