Abstract: Particle swarm optimization is recognized as a classic algorithm simulating swarm intelligence.A new algorithm based on particle swarm optimization is discussed，which uses geometrical Pareto selection algorithm as archiving algorithm for improving the speed and uses multiple-direction search for seeking extreme points.The experimental results show that this algorithm can obtain many enough solutions and is insensitive to steep fronts，fast and more approximated to the true Pareto front.