Dynamic particle swarm optimization based on dynamic distance threshold and regeneration mechanism
基于动态距离阈值和重生机制的动态微粒群优化

Through introducing dynamic distance threshold to standard PSO, two kinds particle between inside and outside the best location were divided into,the former executed concentrated search,the latter did scatter search,which reasonably ba-lanced the both contradiction.This result in that under the circumstance of keeping fundamental stable condition in particle diversity,convergence speed was improved.By regenerating the dead particle without any contribution, this both might suppress effectively reductions of the particle diversity, and could cause the search to jump out local optimization.The simulating experiment have certified that the algorithm can improve not only the convergence but also the particle diversity.