ABSTRACT
In this paper, air-rail intermodal transport is used to evacuate some international aviation hub flights with poor operating efficiency to neighboring airports. The optimal allocation of long-haul flights in airport clusters is studied. The evaluation system of hub airport flights is constructed from four perspectives: hub development, operation efficiency, flight competitiveness, and consumer benefits. The improved entropy weight TOPSIS method is used to evaluate and sort international aviation hub flights and screen the flights to be optimized. Considering the three parties of the airport, airline, and passenger, a multi-objective flight time optimization model is established to maximize the efficiency of airport punctuality, airline market share, and passenger travel cost. Taking the airports in the Yangtze River Delta as an example, a fast non-dominated sorting genetic algorithm with an elite retention strategy is used to solve the problem. The example results showed that the model can effectively evacuate inefficient flights from international aviation hubs to surrounding airports to alleviate congestion at hub airports and promote the collaborative development of airport clusters.
