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基于改进鲸鱼优化算法的离场航班时刻优化

Optimization of Departure Flight Schedule Based on Improved Whale Optimization Algorithm

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【作者】 胡明华于婧怡赵征江斌

【Author】 HU Minghua;YU Jingyi;ZHAO Zheng;JIANG Bin;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics;

【通讯作者】 于婧怡;

【机构】 南京航空航天大学民航学院

【摘要】 面对航空客货运输服务迅速增长、各地机场离港高峰时段拥挤度激增的情况,需要对离场航班进行优化配置,降低高峰时段离场总延误时间,同时保障航空公司申请的航班时刻总偏移。考虑航班时刻唯一性、走廊口流量限制、机场容量限制等因素,建立双目标离场航班时刻优化模型,运用精英反向策略与黄金正弦算法对鲸鱼优化算法(WOA)进行改进后求解。以北京首都国际机场为例,使用AirTOp对优化后的结果进行仿真验证。结果表明:优化后航班平均延误减少77.62%。因此,改进鲸鱼优化算法可以有效降低离港高峰时段延误,增强机场运行效率,合理配置有限的时刻资源。

【Abstract】 Faced with the rapid growth of air passenger and cargo transportation services and the sharp increase in congestion at various airports during peak departure hours, it is necessary to optimize the configuration of departure flights, reduce the total departure delay time during peak hours, and ensure the total deviation of flight schedules applied by airlines. A dual objective departure flight schedule optimization model was established, considering factors such as flight schedule uniqueness, corridor flow limitations and airport capacity limitations. The whale optimization algorithm(WOA) was improved and solved by elite reverse strategy and golden sine algorithm. Taking Beijing Capital International Airport as an example, AirTOp was used to simulate and verify the optimized results. The results show that the average flight delay is decreased by 77.62% after optimization. Therefore, improving the whale optimization algorithm can effectively reduce delays during peak departure hours, enhance airport operational efficiency, and reasonably allocate limited time resources.

【基金】 国家重点研发计划资助项目(2022YFB2602401)
  • 【文献出处】 重庆交通大学学报(自然科学版) ,Journal of Chongqing Jiaotong University(Natural Science) , 编辑部邮箱 ,2024年10期
  • 【分类号】TP18;V355
  • 【下载频次】57
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