Particle Swarm Optimization Based on Number-Theoretical Net

An improved particle swarm optimization algorithm was proposed to fit multi-peaks searching; this algorithm was combined with number-theoretical method. In this algorithm, Number-theoretic net was used to initialize the particles´ position, and for the purpose of multi-peak searching, the evolution equation was modified. The result of PSO is fined by a method named creeping algorithm for improving convergence. The experimental results on several classical functions show that the improved algorithm can get the better results, and the results also indicate that the number theoretical net results the better ability of convergence because of its better randomicity.