基于粒子群优化算法的扇区组合优化

航空运输业的不断发展给终端区容量带来了巨大的挑战。为了降低管制员的工作负荷,增加终端区的容量,对终端区的扇区优化进行研究,建立了终端区空域拓扑结构模型,利用Voronoi图进行终端区单元划分,并计算各航路点的工作负荷,建立扇区优化的数学模型,利用一种排列组合算法进行单元组合,将各单元的目标函数值作为优化函数,并结合粒子群优化算法求得最优解。最后,以成都终端区扇区优化为例进行了验证,证明了粒子群优化算法的有效性,可以很好地应用在以航路点为划分单元的扇区组合优化中。

Sector Optimum Partition Based On Particle Swarm Optimization

The development of air transportation industry brings huge challenge to terminal capacity. In order to lessen air traffic controller workload and increase airspace capability, sector optimum partition of terminal area was studied, airspace topology structure was built, the terminal area could be divided into several units by means of the Voronoi polygon. The workload of each air route points could be calculated, and the mathematical model of sector optimum partition was built. A kind of permutation and combination algorithm was used to recombine the units, the objective function value of each unit was regarded as optimization function, and the optimal solution could be found in combination with the Particle Swarm Optimization. At last, an example of Chengdu terminal sector optimum is given, which shows particle swarm optimization is an effective method to apply into Sector optimum partition based on air route points.