危险天气下进离场航线网络优化

针对危险天气的动态特性,采用卡尔曼滤波对危险天气的未来位置进行预测,为进离场航线的网络优化提供基础,消除其对进离场航线网络的影响。提出先水平后垂直的航路点搜索策略,通过负反馈惩罚因子,加速最优解的收敛速度,实现了三维空间路径搜索蚁群算法。根据航班运行特点,制定优化次序,逐个优化单条航线,实现整个航线网的优化。实验表明,该方案可有效解决危险天气下进离场航线网络优化问题,在保证航线安全性、经济性的同时,算法运行效率明显提高。

Optimization for Arrival and Departure Route Network under Hazardous Weather

Focused on the dynamic feature, Kalman Filter is used to predict the future location of the hazardous weather for the optimization for arrival and departure route network, in order to eliminate the effect to the network. The horizontal-first search strategy is proposed. Combined with negative feedback factor, the cost of computing is lowered and the path search algorithm is realized. Based on the operational characteristics, the route priority is established, with which the single route is optimized individually and then the optimization for the entire route network is accomplished. It is shown that optimization for arrival and departure route network under hazardous weather can be achieved effectively with the solution proposed, and the efficiency of the algorithm is improved significantly, with the safety and economic efficiency being maintained.