Multiple Population Differential Evolution Algorithm and its Application
Xingbao Gao · Jisuanji fangzhen · 2011
The mutation mechanism of differential evolution algorithm does not apply the population information sufficiently,so the mutation operation is blind.Inspired by particle swarm optimization's information sharing mechanism,we propose a multiple population differential evolution algorithm,which divides whole group into many sub-populations,thus the every sub-population's experiences can instruct mutation operation by referring to inner message and outer message,which on one hand,accelerates the convergency;on the other hand,increases diversity of population.The numerical experiment indicated that the new algorithm has the features of stability and strong global exploration ablity,which can solve onstraint optimization problems efficiently.