In light of the escalating frequency of extreme meteorological phenomena and emergent public incidents in recent years, the demand for emergency airlift capabilities has witnessed a marked surge. In order to ensure normal flight operations during the outward dispatch of airline aircraft, a hierarchical solution approach was used to investigate the flight recovery problem faced by airlines participating in emergency transportation due to reduced capacity. It begined with the formulation of a multi-objective integer programming model prioritizes concurrent minimization of cumulative flight delay duration and operational expenditures in disrupted scheduling scenarios, followed by implementation of a bisection search algorithm to determine the minimal permissible delay threshold through constraint stratification. Subsequent development of a flight network topology via arc selection mechanisms incorporated Dijkstra’s algorithm to minimize aircraft substitution frequency, culminating in computational optimization using the Gurobi solver to derive cost-minimal recovery strategies. Finally, the feasibility of the proposed model and algorithm was validated using an airline’s actual flight plan as a case study. The results show that, compared with traditional outward dispatch solutions, the proposed approach improves the flight execution rate by 10.3%, reduces flight cancellations, and offers an effective method for flight schedule optimization.