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飞行冲突解脱是航空器安全运行的关键,粒子群优化(particle swarm optimization,PSO)算法和变邻域搜索(variable neighborhood search,VNS)算法都可以用于解决飞行冲突,但PSO算法接近最优解时收敛速度降低,VNS算法的全局搜索能力较差。为融合PSO算法全局搜索的快速收敛特性和VNS算法的局部搜索能力,提出了变邻域搜索改进的粒子群优化算法。仿真结果证明该算法能够快速搜索到全局最优解,继承了二者的优势,同时提高了最终解脱航迹的适应值,并减少了收敛时间。
Flight conflict relief is the key to the safe operation of aircraft. Both particle swarm optimization (PSO) algorithm and variable neighborhood search (VNS) algorithm can be used to solve flight conflicts. However, when the PSO algorithm approaches the optimal solution The convergence speed is reduced, and the global search capability of the VNS algorithm is poor. In order to integrate the fast convergence property of global search of PSO algorithm and local search ability of VNS algorithm, an improved particle swarm optimization algorithm based on neighborhood search is proposed. The simulation results show that the algorithm can quickly search the global optimal solution, inherit the advantages of both, and improve the fitness of final release trajectory and reduce the convergence time.