Stokastik Fraktal Arama Algoritması ve CMA-ES tabanlı yeni bir hibrit algoritma

In this study, a novel hybridization approach, which is called CMASFS and based on the covariance matrix adaptation evolution strategy (CMA-ES) stochastic fractal search (SFS) algorithms. To make proposed algorithm dynamic, Gaussian walk equations involved in diffusion process of SFS have been updated decide to use equations. The effectiveness tested using CEC2017 benchmark functions having unimodal, multimodal, hybrid, composition 10, 30, 50, 100 dimensions. performance compared with 17 metaheuristic algorithms given literature over functions. According results, it seen that generally obtained better mean error values. Moreover, show superiority algorithm, Friedman analysis Wilcoxon rank-sum test are applied results signed-rank improvement statistically significant majority CEC2017. verify best rank both original other