Stochastic Fractal Dynamic Search for the Optimization of CEC’2017 Benchmark Functions

This article develops an approach for dynamic parameter adaptation in the Stochastic Fractal Search (SFS) method, this by adding a fuzzy inference system for the dynamic adjustment of the diffusion parameter, thus generating the Stochastic Fractal Dynamic Search (SFDS) method. The SFDS implementation was carried out and tested with the optimization of CEC’ 2017 benchmark functions comparing its results with other optimization algorithms.