多跑道协同运行模式优化方法

繁忙机场飞行区运行能力低下导致空中交通拥堵及航班延误现象频发，机场系统亟需扩容增效与排堵保畅。为有效平衡机场容流供需，研究了多跑道协同运行模式优化方法。综合考虑机场布局、交通流特性、气象条件等因素，提出了多跑道协同运行模式分类方法；基于跑道容量包络线理论，通过引入容量损失系数客观反映模式切换特点，建立了多跑道协同运行模式优化模型；结合多目标优化及遗传算法基本理论，设计了带精英策略的非支配排序遗传算法（NSGA），对模型进行了准确求解。仿真实验表明，模型可对多跑道协同运行模式进行优化配置，有效实现机场容量与流量之间的均衡。与单一固定模式相比，多元组合模式优化效果显著，其中航班延误成本减少了38.1%，航班调整数量减少了46.4%，所提方法可显著提升多跑道协同运行能力，有效提高航班正常性。

Optimization Approach for Collaborative Operating Modes of Multi-runway Systems

Low service ability of an airfield area causes frequent air traffic congestion and flight delays at busy airports. The airport system calls for capacity and efficiency improvements urgently to relieve the current congested situation. In this work, an optimization approach for the collaborative operating modes of multi-runway systems is proposed to balance the demand and capacity. Runway operating modes are classified in detail taking into consideration the airport layout, air traffic characteristics, weather conditions and other factors comprehensively. Based on the theory of runway capacity envelope, a corresponding optimization model is established by introducing the capacity loss coefficient which objectively reflects the mode switching characteristics. Then an elitist non-dominated sorting genetic algorithm is designed combined with the multi-objective optimization theory, and applied to solve the problem of multi-runway operating mode configuration. Simulation results show that the above model and algorithm can achieve optimized multi-runway configuration and improve demand-capacity balancing. Compared with the single runway mode, the combined runway modes bring about a striking optimization effect which results in a 38.1% reduction in the cost of flight delays and a 46.4% decrease in the quantity of adjusted flights. The approach provided can significantly enhance collaborative operating efficiency of a multi-runway system, and effectively improve air traffic punctuality.