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The aim of hybridization in the context of evolutionary computation is to combine appropriate operators from different evolutionary computation paradigms to form a single technique that enjoys a statistically superior performance over a wide range of optimization problems. This paper introduces a novel hybridization between differential evolution and update processes of the stochastic fractal search algorithm. The diffusion property of the fractal search algorithm is applied in random fractals followed by two novel update processes to explore the search space more efficiently. In this algorithm, a diffusion process based on differential evolution algorithm is used instead of random fractals in the original stochastic fractal search algorithm. A new success-based scheme is used to utilize the update processes and to solve the burden of extra computations during the search. This new algorithm captures the strengths of both …