%0 Journal Article
%A YUAN Luo1
%A 2
%A GE Hongwei1
%A 2
%T Dispersion Particle Swarm Optimization Algorithm Based on Random Whip Mechanism
%D 2019
%R 10.3778/j.issn.1002-8331.1803-0106
%J Computer Engineering and Applications
%P 66-71
%V 55
%N 4
%X The Particle Swarm Optimization（PSO） has problems as being trapped in local minima due to premature convergence and weakness of global search capability. To overcome these disadvantages, Dispersion Particle Swarm Optimization Algorithm based on Random Whip Mechanism（EGPSO） is proposed. Firstly, the concept of particles’ dispersion is presented. In order to avoid falling into local optimum, the algorithm determines the state of the loose particles and marks them by evaluating the dispersion of each particle dynamically, and then uses random whip mechanism to deal with loose particles. Secondly, in order to further improve the algorithm’s convergence speed and accuracy, EGPSO handles active particles by using the optimal location of history. Experimental results on eleven standard benchmark functions demonstrate that EGPSO outperforms original PSO and the other related algorithms in terms of the solution quality and the stability.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1803-0106