Gender-hierarchy particle swarm optimizer based on punishment

Abstract

The paper presents a novel particle swarm optimizer (PSO), called gender-hierarchy particle swarm optimizer based on punishment (GH-PSO). In the proposed algorithm, the social part and recognition part of PSO both are modified in order to accelerate the convergence and improve the accuracy of the optimal solution. Especially, a novel recognition approach, called general recognition, is presented to furthermore improve the performance of PSO. Experimental results show that the proposed algorithm shows better behaviors as compared to the standard PSO, tribes-based PSO and GH-PSO with tribes. © 2010 Springer-Verlag.