【摘要】 为研究考虑航空公司航班公平性的离场航班恢复问题，首先，根据某机场历史数据，研究了不确定因素对机场容量的影响，并通过贝叶斯网络得到天气等不确定因素对航班恢复过程中过站时间的影响。其次，在考虑航班优先级的基础上，构建以最小化总延误时间和基于基尼系数确定的航空公司公平性的多目标航班恢复调度模型，并且将不确定性因素对机场容量和过站时间的扰动加入到模型中。最后，运用NSGA-Ⅱ算法对国内某机场的航班数据进行算例分析，与先到先服务方法进行对比。结果表明，总延误时间降低了37.2%,航空公司公平性由0.440提升至0.202,所建模型对扰动的吸收性能较好，验证了模型和算法的可行性。更多还原

【Abstract】 In order to study the problem of departing flight recovery considering airline flight fairness, firstly, according to the historical data of an airport, the influence of uncertain factors on airport capacity was studied, and the influence of uncertain factors such as weather on the turnaround time during the flight recovery process was obtained through Bayesian network. Then, a multi-objective flight recovery scheduling model was constructed to minimize total delay time and determine the fairness of airlines based on the Gini coefficient. In addition, the disturbance of the uncertainty factor to the airport capacity and turnaround time was added to the model. Finally, the NSGA-Ⅱ algorithm was used to analyze the flight data of a domestic airport and compare it with the first come first service method. The results show that the total delay time is reduced by 37.2%, the airline fairness is improved from 0.440 to 0.202, and the built model has better absorption performance of disturbance, which verifies the feasibility of the model and algorithm.更多还原