基于优先级调配的进离场航班序列动态优化  

Dynamic optimization of arrival and departure flights sequence based on priority allocation

作　　者：王莉莉[1] 胡畔[1] 

机构地区：[1]中国民航大学空中交通管理学院,天津300300

出　　处：《飞行力学》2016年第4期90-94,共5页Flight Dynamics

基　　金：国家自然科学基金与中国民用航空局联合资助(61179042);中央高校基本科研经费资助(ZXH2012L005)

摘　　要：以可变的优先级作为调配手段,针对航班的进离场序列建立了一种动态优化模型。首先,根据不同进离场阶段的航空器燃油消耗率和安全系数,进行航班初始优先级分配;然后,考虑机场的空中等待航班数量、空域容量、场面容量以及机场的起飞需求,对航班优先级进行二次调配。以总耗油量为目标函数,引入合作型协同进化遗传算法,设计了令一对代表个体形成合作团体的新的代表个体选择方案,改善传统遗传算法中存在的种群多样性低、易早熟等问题。仿真结果表明,在机场容量限制下,该模型仍可以实现流量的动态调配,并有效降低燃油消耗,缓解机场空域及场面的运行压力。Through allocated methods of variable priority,this paper established a dynamic optimization model for sequence of arrival and departure flights. Firstly,according to fuel consumption and safety factor of aircraft,locating in different arrival and departure stages,initial priorities were distributed for flights. And then,the priorities were deployed the second time considering the number of flights waiting over the airport,the airspace capacity,the surface capacity and the departure demand of the airport. And objective function is minimum total fuel consumption,Cooperative Co-evolutionary Genetic Algorithm（ CCGA） was introduced and it adopted a certain method that made a double represents form into a cooperative group which solves the problems,e. g. low species diversity and easy to be premature of traditional genetic algorithm. Simulation results indicate that this model can achieve dynamic allocation of airport flow under airport capacity limits,relieve the pressure on airport airspace and scene operation and reduces total fuel consumption.

关 键 词：合作型协同进化遗传算法 动态优化 优先级调配 容量限制 

分 类 号：V355.1[航空宇航科学与技术—人机与环境工程]