基于遗传算法的多扇区移交点交通流量优化

以扇区之间的移交点为研究对象,在扇区容量受限的情况下,将尾随间隔(MIT)与时隙分配相结合对进入扇区的航班流量进行优化管理,以保证扇区之间的航班运行通畅。以最小航班累积延误成本为目标函数,并通过流量分配得出移交点的MIT,同时使用遗传算法优化在满足MIT的情况下航班通过移交点进入扇区的顺序,并求得最低延误成本,得到的最低延误成本比使用先到先服务的传统策略所得到的延误成本降低了18. 6%。

Traffic Flow Optimization of Multi-sector Handover Points Based on Genetic Algorithm

This article takes the handover point between sectors as the research object, When sector capacity is limited, the Miles-in-Trail (MIT) and time slot allocation are combined to optimize the management of the flight traffic entering the sector to ensure that flights between sectors are running smoothly.Taking the minimum flight cumulative delay cost as the objective function, and obtaining the MIT of the handover point through traffic distribution, at the same time, the genetic algorithm is used to optimize the order of the flight entering the sector through the handover point when the MIT is satisfied, and obtained the minimum delay cost ,which was reduced by 18.6% compared to the delay cost of the traditional strategy of using first-come, first-served services.