Particle swarm optimizer with finite velocity of information transmission

Abstract

Particle Swarm Algorithm is based on the capacity of the particles which integrate the swarm to share and to communicate relevant information about the best positions visited: localbest and globalbest. Independently of the position of the particles, all particles know the best position visited by any other particle in the same time-step when it is reached. However, in real world, information transmission has to take some time to travel between two particles positions. In this paper, the effect of a finite velocity for information transmission on the performance of the Particle Swarm Algorithm is analysed. Two scenarios appear in this context; first at all, when the velocity of information transmission is almost equal to the maximum velocity of the particles; and the second one, when it is much larger. This study clarifies the role played by a finite velocity of information transmission in the performance of the algorithm, specially when it is almost equal to the maximum velocity of the particles.