Considering three-stage scheduling optimization of multi-type flight refueling vehicles with time windows

To address the issue of inefficient refueling vehicle scheduling during airport flight support operations, this study establishes dual constraints for flight refueling time windows and permissible commencement time windows while prioritizing flight safety. It creates three integer programming models that optimize refueling vehicle allocation under these two limitations, standardizes stand designations and apron positions, and looks at key variables in three operational situations. According to the actual operation of the airport, a genetic optimization algorithm with elite strategy was proposed to solve the model according to the actual operation of the airport. In the first stage of independent scheduling, an evaluation mechanism that takes into account the two abilities of adaptability and population diversity was designed to ensure the diversity of the population. In the second and third stages of collaborative scheduling, a penalty factor introduction algorithm is designed, which can effectively avoid the emergence of populations that do not meet the target constraints. The simulation results show that compared with the traditional manual scheduling and genetic algorithm, the number of dispatched fuel trucks is reduced by 27.6% and 21.8% on average, which can provide effective decision support for airport fuel truck scheduling.