基于粒子群算法的飞行冲突解脱问题  

Study on Resolution of Flight Conflicts Based on Particle Swarm Optimization

作　　者：王洁宁[1] 袁志娟[1] 

机构地区：[1]中国民航大学空中交通管理研究基地,天津300300

出　　处：《中国民航大学学报》2010年第4期1-4,共4页Journal of Civil Aviation University of China

基　　金：国家自然科学基金项目(60832011);中国民航大学博士启动基金项目(06QD07S)

摘　　要：自由飞行可有效解决航线日益加剧的拥挤问题,但同时也增加了管制员管制监控的难度,从而使飞行冲突探测和解脱成为自由飞行的关键问题。粒子群算法(particle swarm optimization)是一种群智能优化算法,尝试将其应用于飞行冲突解脱问题,构造了适合飞行冲突解脱问题的粒子表达方式,建立了冲突解脱问题的粒子群算法,成功解决了飞行冲突,并将其运行结果与遗传算法结果作了对比试验。实验结果表明,粒子群算法是求解飞行冲突解脱问题的一个较好方案。Free flight is a conceptual operation in solving the increasing air traffic congestions; however it would make the air controller more difficult to make decisions to optimize conflict resolution. PSO（particle swarm optimization） is a swarm intelligence optimization. In this paper, PSO is attempted to be used to solve the conflict resolution. This paper proposes a novel particle presentation for the conflict resolution, establishes a PSO algorithm for this kind of problem, solves the conflict in flight successfully, and compares with GA in the same conflict resolution experiments. Experimental results show that the PSO is an effective method in solving the conflict resolution problem.

关 键 词：空中交通管理 飞行冲突探测与解脱 粒子群算法 自由飞行 遗传算法 

分 类 号：V355.1[航空宇航科学与技术—人机与环境工程]