Particle swarm optimization using velocity control

This paper presents a new Particle Swarm Optimization (PSO) technique using velocity control. In PSO, when a particle finds a local optimal solution, all of the particles gather around it, and cannot escape from it. In the proposed method, we lead the particles from intensification to diversification by adding a random number to the velocity of the particles depending on the distance from gbest, and thereby the particles can search widely in the search space. Moreover, the velocity may not change so much occasionally because the average of random numbers added to velocity is 0. So, we restrain update of pbest of particles depending on the distance from gbest, too. Then the proposed method is validated through numerical simulations with several functions which are well known as optimization benchmark problems comparing to some PSO methods. © 2009 The Institute of Electrical Engineers of Japan.