Abstract
Topology plays an important role for Particle Swarm Optimization (PSO) to achieve good optimization
performance. It is difficult to find one topology structure for the particles to achieve better optimization
performance than the others since the optimization performance not only depends on the searching abilities of the
particles, also depends on the type of the optimization problems. Three elitist set based PSO algorithm without
using explicit topology structure is proposed in this paper. An elitist set, which is based on the individual best
experience, is used to communicate among the particles. Moreover, to avoid the premature of the particles, different
statistical methods have been used in these three proposed methods. The performance of the proposed PSOs is
compared with the results of the standard PSO 2011 and several PSO with different topologies, and the simulation
results and comparisons demonstrate that the proposed PSO with adaptive probabilistic preference can achieve
good optimization performance.