A collaborative decision making framework for airline irregular flight recovery with network manager disruption coordination

Hub-and-spoke networks are widely employed by airlines to enhance operational efficiency; however, their structural dependence renders them highly vulnerable to disruptions, which can trigger significant delays across the network. Conventional disruption management, typically conducted independently by airlines and the network manager (NM), often leads to suboptimal recovery due to limited coordination. This paper addresses the irregular flight recovery problem under the disruption coordination between airlines and the NM. To this end, a Collaborative Decision Making (CDM) framework is proposed, which consists of four phases with airlines and the NM alternatively adjusting recovery schedules. First, a revisited recovery model is developed for airlines to generate initial and alternative recovery schedules with the consideration of updated airport slot capacities shared by the NM. Next, an airline-driven Air Traffic Flow Management model is designed for the NM which accepts two recovery schedules from each airline in line with their operational preferences, and then selects and adjusts the schedules if needed. To balance efficiency and fairness concerns, a fairness mechanism is further introduced to regulate the number of reversed flight pairs. Finally, experiments are conducted on 32 different scenarios derived from realistic datasets of Chinese airlines under the disruption of airport capacity reduction. Results demonstrate that the proposed CDM framework yields alternative schedules with lower recovery costs and higher airline preferences. By allowing airlines to submit multiple schedules, the NM can select and adjust schedules which better reflect airlines’ operational concerns. The inclusion of fairness considerations provides additional flexibility in balancing efficiency and equity.