A Particle Swarm Optimization with Stagnation Detection and Dispersion
Chukiat Worasucheep · 2008
Particles or candidate solutions in the standard particle swarm optimization (PSO) algorithms often face the problems of being trapped into local optima. To solve such a problem, this paper proposes a modified PSO algorithm with the stagnation detection and dispersion (PSO-DD) mechanism, which can detect a probable stagnation and is able to disperse particles. This mechanism will be described and its performance is evaluated using eight well-known 30-dimensional benchmark functions that are widely used in literature. The results show a promising alternative path for solving the common problem of local optima in PSO algorithms.