摘要
综合考虑机场的空中等待航班数量、空域容量、场面容量以及机场起飞需求等约束条件,以可变的优先级为调配手段,以总延误时间最短为目标函数,建立了一个新的基于容流匹配的进离场航班调度优化模型。引入合作型协同进化遗传算法,设计了用一对代表个体形成合作团体的新选择方式,有效解决了传统遗传算法种群多样性低、易早熟等问题。仿真结果表明,该模型能够在满足机场容量限制的同时,有效降低航班的总延误时间。
Through allocated methods of variable priority,a new arrival and departure scheduling optimization model based on the matching of the traffic flow with the capacity is established with an objective of minimum total delay time subject to constraints,i.e.,the number of flights waiting in the airport,the airspace capacity,the surface capacity and the departure demand of the airport.A new selection method based on the cooperative co-evolutionary genetic algorithm is established using apair of represents to form a cooperative group,which can effectively solve the low population diversity and premature of traditional genetic algorithm.The simulation results indicate that the model can effectively reduce the total delay time of the flights and meet the capacity limit requirement of the airport.
出处
《南京航空航天大学学报》
EI
CAS
CSCD
北大核心
2015年第6期827-832,共6页
Journal of Nanjing University of Aeronautics & Astronautics
基金
国家自然科学基金委与中国民用航空局联合(61179042)资助项目
中央高校基本科研经费(ZXH2012L005)资助项目
关键词
空中交通流量管理
合作型协同进化遗传算法
进离场航班序列优化
客流匹配
代表个体
air traffic flow management
cooperative co-evolutionary genetic algorithm
scheduling optimization for arrival and departure flights
matching of capacity with flow
represents
