摘要
本文建立了停机位分配的多商品网络流模型,并以航空器总场面运行时间最小为目标,建立数学模型。将机场场面分为若干区域,建立区域—机位两级分配策略,以降低问题规模。设置机位外等待时间,以省去区域容量相关约束。在传统粒子群算法的基础上,设计离散粒子群算法,对模型进行求解。选取乌鲁木齐机场某日240架航班和109个机位进行实验,证明了与现有研究中的典型模型相比,多商品网络流模型能使运算时间减少10.1%,并能达到与典型模型相同的精度。全空域和机场模型(total airspace and airport modeller,TAAM)仿真结果表明,和现行机位分配方案相比,多商品网络流模型的机位分配结果能使航空器的场面调配运行时间减少7.49%,延误时间减少8.87%。算例结果进一步表明,提高机场场面运行效率的关键在于均衡航班的进离港滑行距离,同时避免停机位密集分布。
A multi-commodity network flow model for gate allocation was developed,and a mathematical model was established with the objective of minimizing the total aircraft ground operation time.Divided the airport field into zones and established a two-level zone-gate allocation strategy to reduce the size of the problem.Set the out-of-gate waiting time to omit the regional capacity related constraint.Based on the traditional particle swarm algorithm,a discrete particle swarm algorithm was designed to solve the model.240 flights and 109 gates at Urumqi Airport on a certain day were selected for experiment.The experimental results demonstrate that multi-commodity network flow model can reduce the computing time by 10.1%and achieve the same accuracy as the classic model in existing studies.The TAAM(total airspace and airport modeller)simulation results show that the gate assignment results of the multi-commodity network flow model can reduce the ground allocation operation time of aircrafts by 7.49%and delay time by 8.87%compared with the current slot assignment plan.The results of the example further show that the key to improving the efficiency of airport ground operation is to balance the arrival and departure taxiing distance of aircrafts,while avoiding a dense distribution of gates.
作者
朱承元
于海波
ZHU Cheng-yuan;YU Hai-bo(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)
出处
《科学技术与工程》
北大核心
2023年第10期4417-4425,共9页
Science Technology and Engineering
基金
工信部民用飞机专项科研项目(MJ-2020-S-03)。
