Integrated recovery of air cargo transportation under various abnormal scenarios

Freighter airlines face significant challenges in restoring flight, aircraft and cargo schedules during disruptions. Traditionally, these challenges are addressed using a sequential approach, where flights, aircraft, and cargo operations are reinstated step by step, leading to incompatibility and resource wastage. This research introduces a comprehensive strategy for integrated recovery of air cargo transportation under various abnormal scenarios, where both aircraft and cargo recovery are considered, and different transportation modes (e.g., freighter flights, belly flights, and trucks) are utilized. A novel string-based model is proposed to decompose and solve the integrated air cargo recovery problem. The model explores the complexities arising from multiple abnormal scenarios and considers cargo timeliness with different transportation modes (e.g., freighter flights, belly flights, and trucks), aligning the recovery process more closely with real-world operations. A heuristic-based column-and-row generation algorithm is proposed based on properties of the model. Moreover, a series of inequality constraints and integer processing mechanisms are designed, which significantly reduces the solution gap between mixed-integer-program model and linear relaxation of model. The performances of the proposed model and algorithms are shown in the experiments based on two real world datasets under four scenarios from the largest freighter airline company in China.