基于自适应遗传算法的机场场面优化研究  

Research on Airport Field Optimization Based on Adaptive Genetic Algorithm

作　　者：钟子涵 朱培 陈志浩 马尚 邵荃[1] ZHONG Zi-han;ZHU Pei;CHEN Zhi-hao;MA Shang;SHAO Quan(Nanjing University of Aeronautics and Astronautics,Nanjing 210000,China;Guangzhou Baiyun International Airport Operation and Control Centre,Guangzhou 510000,China)

机构地区：[1]南京航空航天大学,江苏南京210000 [2]广州白云国际机场运行控制中心,广东广州510000

出　　处：《航空计算技术》2024年第6期81-86,共6页Aeronautical Computing Technique

基　　金：国家自然科学基金委员会-中国民用航空局民航联合研究基金项目资助(U2233208)。

摘　　要：为提高机场场面运行效率,降低航空器延误与滑行时间,提出了基于机场场面联合调度的双层模型。该模型考虑跑道和滑行道之间的关系,以进离场顺序为上层规划,以滑行路径调度为下层规划进行建模,通过上下层模型协同调度来提高机场场面运行效率。设计自适应遗传算法对模型进行求解,自适应遗传算法通过动态调整交叉概率和变异概率,提高了算法的收敛精度和速度。通过国内某大型机场运行数据进行仿真验证。结果表明,该模型能够有效优化航班时刻分配和滑行路径分配,为机场场面联合调度提供决策支持。In order to improve airport field operation efficiency and reduce aircraft delay and taxiing time,this paper proposes a bi-level model based on joint scheduling of airport field.The model considers the relationship between runway and taxiway,and is modelled with approach and departure sequences as the upper layer planning and taxi path scheduling as the lower layer planning,so as to improve the efficiency of airport field operation through the joint scheduling of the upper and lower layer models.The adaptive genetic algorithm,designed to solve the model,dynamically adjusts crossover and mutation probabilities to enhance convergence accuracy and speed.Simulation is carried out to verify the model using operation data from a large domestic airport.The results show that the model can effectively optimize flight time allocation and taxi path allocation,providing decision support for joint airport field scheduling.

关 键 词：跑道排序 滑行道调度 联合调度优化 双层规划模型 自适应遗传算法 

分 类 号：V351[航空宇航科学与技术—人机与环境工程]