Research on Particle Swarm Optimization with Dynamic Inertia Weight

Particle swarm optimization (PSO) is a novel stochastic optimization algorithm based on the study of migration behaviors of bird flock in the process of searching food. Inertia weight, as an important parameter in PSO algorithm, plays a very important role in controlling the exploitation and exploration ability of algorithm. Recently, much more attention has been paid to the research of modified PSO based on dynamic inertia weight. This paper simply introduces the principle of PSO and overviews the research advances about dynamic inertia weight in existing references.