An Improved Particle Swarm Optimization with New Select Mechanism

Abstract

The particle swarm optimization is a stochastic, population-based optimization technique. A modified PSO algorithm is proposed in this paper to avoid premature convergence with the new select mechanism. This mechanism is simulating the principle of molecular dynamics, which attempts to activate all particles as the most possible along with their population evolution. Two stopping criteria of the algorithm are derived from the principle of energy minimization and the law of entropy increasing. The performance of this algorithm is compared to the standard PSO algorithm and experiments indicate that it has better performance.