Aircraft Route Planning Based on Improved Particle Swarm Optimization Algorithm

The particle swarm optimization is widely used in optimization questions for its advantage of simply realized, high precision, small adjusted parameter and quick convergence velocity. The article analyses their influences of inertia and acceleration gene to optimization capability of particle swarm optimization and brings forward the improved means of dynamicly modulating the inertia gene which will improve the global and individual search capability. The simulation indicates that the impoved arithmetic is obviously enhanced in search velocity and precision.