Integrated Aircraft and Passenger Recovery With Enhancements in Modeling, Solution Algorithm, and Intermodalism
Fang Sun, Hong Liu, Yu Zhang
Abstract
During schedule disruption of airline operations, aircraft assigned to some flights become unavailable (are held on the ground) for a certain time period. An effective recovery plan becomes essential for airlines to reduce potential losses and prevent the propagation of disruption and delay. In this study, we addressed integrated aircraft and passenger recovery for such schedule disruption. In addition to modeling and reducing the size of model for solving the problem efficiently with modified time-band network and candidate passenger itinerary generation, we also introduce an intermodal concept to expand airline aviation networks by including ground transportation modes. With this intermodal network, airlines would have more flexibility for performing aircraft recovery based on business interest priorities and would protect passengers from suffering extensive delays. We applied the modeling to a pure aviation network and the intermodal network and compared both outcomes with those from the existing literature. The comparison shows that the algorithms generating the modified time-band network can reduce redundant arcs in the network and, thus, the feasible solution space of mix integer linear programming (MILP) without compromising optimality. Considering a real-time intermodal network in disruption management helps to reduce the number of stranded passengers and the total disruption cost.