Abstract
At present, hub airport is facing a lot of emergency situations, e.g., the management of irregular flight, which affects the sustainable development of the airport. Most of the methods for evaluating the robustness of airport gate assignment have been proposed by giving an independent evaluation function based on their experience, and thus, subjective factors are involved in varying degrees. Therefore, this paper puts forward an objective evaluation method based on the analysis of airport flight arrival, which gives a digital transformation strategy for the airport resource scheduling. A novel evaluation method based on data analysis of flight arrival time, and a mathematical model are formulated accordingly. In order to solve the proposed NP-hard problem, a new hybrid genetic algorithm combined with a heuristic algorithm is designed. In numerical experiments, the actual flight data of an international hub airport are used to analyze and verify the effectiveness of the proposed method. The results showed the advantages in scheme stability, operating cost savings, and risk reduction of the proposed method.
Highlights
Air transportation and maritime transportation are the main parts of international freight transport [1, 2]
Airport gate assignment (AGA) is about finding an assignment of flight to terminal or ramp positions called gate, and it is a key activity in airport operations [4]
Airport gate assignment is generated in advance based on the flight initial schedule, including the number of flights, departure/arrival time, and flight’s ground service time [5]
Summary
Air transportation and maritime transportation are the main parts of international freight transport [1, 2]. E flight irregular arrival poses tremendous challenges to airport management in airline recovery (flight recovery, aircraft recovery, crew recovery, and airport gate plan recovery) and passenger arrangement. Bolat [11] formulated a mathematical model with a quadratic function for minimizing the variance of idle time at the gates to make the initial assignments insensitive to variations in flight schedules. Diepen et al [13] have given a cost function based on the idle time between consecutive flights to evaluate the robustness of the AGA plan 10. Is paper proposed an assignment robustness evaluation approach, which is based on the analysis of airport flight irregular arrival patterns, and the author’s subjective factors are ignored to an extent. The real data of an international hub airport are used to analyze on the RAGA model and its robustness is provided
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