摘要
以往相关飞机地面滑行预测的研究大都集中在滑行时间的预测上,然而系统的研究不仅是预测时间,也应估计相关的成本,如燃料燃烧。为此,通过多目标免疫优化的方法分开讨论滑行道不同部分,得到一组沿各段不同的滑行轨迹,这些轨迹提供了飞机滑行时间的预估,且有很大的潜力可整合到滑行道优化路由和调度过程中,在降低总滑行时间和油耗的同时找出最佳滑行路径。
To find more efficient way of airport working,a very important element is to accurate estimate the ground movement.Previous researches concentrated on the estimation of aircraft taxi time.However,such a concept should be stretched more than just predicting time.It should also be able to estimate the associated cost,e.g.fuel burn.Hence,an immune inspired multi-objective optimization method was employed to investigate such trade-offs for different segments along taxiways,which led to a set of different taxiing trajectories for each segment.Each of these trajectories,on the one hand,provides an estimation of aircraft taxi time,and on the other hand,has great potential to be integrated into the optimal taxiway routing and scheduling process in a bid to find out the optimal taxiing in terms of not only reducing total taxi time but also lowering fuel consumption.
出处
《计算机工程与设计》
北大核心
2016年第5期1224-1228,共5页
Computer Engineering and Design
基金
国家自然科学基金委员会与中国民用航空局联合基金项目(U1233124)
中央高校基金项目(3122014P003)
关键词
多目标免疫算法
飞行器地面运动
最优滑行路径
燃料消耗
滑行时间
multi-objective immune algorithm
aircraft ground movement
optimal taxiing trajectories
fuel consumption
taxi time
