Abstract:

In recent years， the air passenger and cargo transport business in China has surged. Many large civil aviation companies not only carry passenger traffic but also utilize the belly holds of passenger aircraft to transport a significant amount of cargo， with the growth rate of cargo volume far exceeding that of dedicated freighters， making it one of the main modes of air transport. However， abnormal flights caused by weather， maintenance， and other factors can lead to simultaneous disruptions in both passenger and cargo itineraries， resulting in more complex recovery operations for airlines. In response to this， an integrated passenger and cargo flight disruption recovery model is first established， utilizing time-space network technology to depict the transfer networks for aircraft， passengers， and cargo. Furthermore， for the cargo transfer network without transfer limit constraints， disruption-clearing strategies （DCS） and limited generation-augmentation strategies （LGAS） are proposed to enhance solution efficiency. Subsequently， a case study using real data is conducted， comparing the integrated recovery model with a non-integrated model， revealing significant advantages in cost savings for recovery in the proposed integrated model. Finally， the reasons for redundant calculations in cargo recovery are analyzed and the process is optimized using the proposed strategies， finding that DCS can reduce solution time with almost no increase in cost， while LGAS can further improve computational efficiency and has specific usage techniques.

Key words: flight disruption recovery, aviation logistics, passenger and cargo integration, time-space network