Difference brain storm optimization algorithm based on clustering in objective space
WU Ya-li
FU Yu-long
WANG Xin-rui
LIU Qing
Abstract：As a new kind of swarm intelligence optimization algorithm,brain storm optimization(BSO)has paid more attention of more researchers in different fields.Based on the cluster operation and mutation of original BSO,a novel BSO algorithm named difference brain storm optimization based on clustering in objective space(DBSO-OS)is proposed in this paper to improve the performance of the original BSO algorithm.The clustering operation is designed in objective space which can decrease the computation complexity comparing with clustering in decision space in the proposed algorithm.The difference mutation operation is adopted to increase the diversity of the population.The simulation results of many benchmark functions of different dimensions demonstrate that the proposed algorithm can not only improve the time perfor-mance but also the precision.Moreover,the suitable parameter selection strategy is provided on the basis of the parameter analysis of the proposed algorithm.And the combined heat and power economic dispatch(CHPED)are implemented to evaluate the effectiveness of the proposed algorithm.
Keywords：brain storm optimization(BSO)clusterdifference mutationobjective space
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：11( 1583-1593 )