Abstract
Abstract:
A new particle optimization algorithm with dynamic
topology is proposed based on ‘small world’ network. The
technique imitates the dissemination of information in a ‘small
world network’ by dynamically updating the neighborhood
topology of particle swarm optimization. The proposed dynamic
neighborhood strategy can effectively coordinate the exploration
and exploitation ability of particle swarm optimization.
Simulations demonstrated that convergence of the swarms is
guaranteed. Experiments demonstrated that the proposed
method maintained the population diversity and enhanced the
global search ability.