Entropy Based Genetic Algorithm with Dual Subpopulations
Yang Xiao · 2005
An entropy based genetic algorithm with dual subpopulations is proposed in this paper. Two separated subpopulations are generated by using the information entropy theory, and the makimum entropy of genetic population helps to obtain the diversified individuals. In one population, high mutation rate and entropy based selection enhance the exploration ability. In the other Population, dynamic decreased mutation rate is adopted in order to obtain good exploitation ability. Also the immigration between the two populations balances the exploration and exploitation ability. The experimental results show that the proposed method can gain higher global convergence rate and higher speed.