No Velocity Particle Swarm Optimiser with Forgetting Factor and Center

A no velocity particle swarm optimiser with forgetting factor and center is presented. In the algorithm, the position of a particle is influenced not only by the personal best position and global best position but also by the swarm´s center , and a particle has only position without velocity similar to bare bones PSO. The proposed algorithm determined by four real parameters is theoretically analyzed using stochastic process theory. The stochastic convergent condition of the algorithm and corresponding parameter selection guidelines are derived. The algorithm is the simpler and more effective owing to discarding the particle velocity and using the swarm´s center information. The simulation experimental results indict that the algorithm achieves better solutions and faster convergence for some well-known benchmarks.