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为了提升大型繁忙机场的运行效率,考虑了多跑道的运行条件和安全要求等因素,以最小航班总延误为目标函数,以最大位置偏移为约束条件,引入滚动时域控制策略,建立了航班动态排序模型。针对多跑道航班调度问题的特点,分别采用基于滚动时域控制策略的遗传算法和现有的先到先服务算法求解模型。计算结果表明:当航班正常时,采用现有的先到先服务算法,航班总延误为1 712s,采用基于滚动时域控制策略的遗传算法,航班总延误为1 080s,与先到先服务算法相比,延误时间减小37.0%;当航班不正常时,采用现有的先到先服务算法,航班总延误为1 658s,采用基于滚动时域控制策略的遗传算法,航班总延误为969s,与先到先服务算法相比,延误减小41.5%。可见,基于滚动时域控制策略的遗传算法有效。
In order to improve the efficiency of large-scale airport, considering the operating conditions and safety requirements of multi-runway and other factors, the total delay of minimum flight is taken as the objective function and the maximum position offset is used as constraint. The rolling time-domain control strategy is introduced to set up the flight Dynamic sorting model. Aiming at the characteristics of multi-runway flight scheduling problems, the genetic algorithm based on rolling time-domain control strategy and the existing first-come-first-serve algorithm are respectively used to solve the model. The calculation results show that when the flight is normal, the existing first-come-first-serve algorithm is used, the total flight delay is 1 712s, the genetic algorithm based on rolling time-domain control strategy is adopted, the total flight delay is 1 080s, and the first- The delay time is reduced by 37.0%; when the flight is not normal, the existing first-come-first-serve algorithm is used, the total flight delay is 1 658s, the genetic algorithm based on rolling time-domain control strategy is adopted, the total flight delay is 969s, Compared with the first-come-first-serve algorithm, the delay is reduced by 41.5%. It can be seen that the genetic algorithm based on rolling time-domain control strategy is effective.