It is well known that the Particle Swarm Optimization (PSO) algorithm easily falls into the local optimal solution.In this paper

we defined a concept of PSO particle-search center

and analyzed the probability density of the center between global and local optimal solutions in random state.A uniform searching particle swarm optimization (UPSO) algorithm whose particle-search center uniformly distributed between local and global optimal solutions is proposed based on that analysis.By analyzing the comparative experiments between UPSO and PSO algorithm with seven benchmark functions

we found that the UPSO and its improved algorithms are more stable and can improve the convergence efficiency in function optimization

especially in non-uniformly multimodal function optimization.