Memetic differential evolution based on fitness Euclidean-distance ratio
Boyang Qu, Jing Liang, Junming Xiao, Z. G. Shang · 2014
In this paper, a differential evolution algorithm based on fitness Euclidean-distance ratio which was proposed to maintain multiple peaks in the multimodal optimization problems was modified to solve the complex single objective real parameter optimization problems. With the fitness Euclidean-distance ratio technique, the diversity of the population was kept to enhance the exploration ability. And in order to improve the exploitation ability, the Quasi-Newton method was combined. The performance of the proposed method on the set of benchmark functions provided by CEC2014 competition on single objective real-parameter numerical optimization was reported.