Research on the recovery method of disrupted flights considering passenger transfer and cancellation costs

In the face of extreme weather conditions, airport closures, or other circumstances, airlines often experience disruptions to their flight schedules, leading to the frequent operational challenge of disrupted flight recovery. The foundational model for disrupted flight recovery aims to recover as many flights as possible with minimal costs, typically encompassing aircraft re-routing and re-timing costs, aircraft maintenance costs, crew reassignment costs, and passenger transfer costs. Existing studies generally estimate these costs using fixed rates. In reality, the first three costs for airlines tend to remain relatively stable. However, different passenger transfer methods can result in significant cost variations, a focal point for ground service personnel during disrupted flight recovery. We conducted a detailed analysis of the cost combinations associated with various passenger transfer methods, including ticket refunds, overnight stays, rebooking on the same airline, and rebooking on other airlines. We established a comprehensive disrupted flight recovery model that considers the three relatively fixed costs and variations in passenger transfer costs, thereby enhancing the resilience of the traditional model based on passenger transfer methods. To solve this model, we employed an enhanced heuristic large-scale neighborhood search (LNS) algorithm. Simulation experiments on airline datasets demonstrated that recovering all disrupted flights primarily through passenger transfer is not necessarily the least costly scenario. The optimal flight recovery ratio depends on passenger refund rates and rebooking methods. By judiciously controlling passenger transfer methods and the recovery proportion of disrupted flights, comprehensive recovery costs for both flights and passengers can be reduced. The research findings not only provide theoretical support for airlines but also offer practical guidance for strategy formulation, improving passenger satisfaction, and controlling operational costs.