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传统航空公司机组配对模型大多是确定的,然而实际上航班通常会受各种不确定因素影响,影响旅客的出行。本文考虑成本以及时间为随机因素,将机组排班的配对寻优建成以成本最小和旅客满意度最大为目标构造混合智能算法来寻找最优解。案例研究的结果显示,模型和算法对于实际中机组配对的寻优是可行的。
The traditional airline crew matching model is mostly determined, however, in fact, the flight is usually affected by various uncertainties, affecting the travel of passengers. In this paper, considering the cost and time as stochastic factors, the pairing optimization of flight scheduling is constructed to find the optimal solution with the goal of minimizing the cost and satisfaction of passengers. The results of the case study show that the model and algorithm are feasible for the optimization of crew pairing in practice.