Particle Swarm Optimization Algorithm with Reverse Thinking Particles

The particle swarm optimization algorithm is a kind of intelligent optimization algorithm. This algorithm is prone to be fettered by the local optimization solution when the particle’s velocity is small. This paper presents a novel particle swarm optimization algorithm named particle swarm optimization with reverse thinking particles which is guaranteed to converge to the global optimization solution with probability one. And we also make the global convergence analysis. Finally, two function optimizations are simulated to show that the PSORTP is better and more efficient than the PSO with inertia weights.