Differential evolution using fuzzy logic and a comparative study with other metaheuristics

Abstract

This paper proposes an improvement to the algorithm differential evolution (DE) using fuzzy logic. The main contribution of this work is to dynamically adapt the parameter of mutation (F) using a fuzzy system, with the aim that the fuzzy system calculates the optimal parameters of the DE algorithm for obtaining better solutions, in this way arriving to the proposed new fuzzy differential evolution (FDE) algorithm. In this paper, experiments are performed with a set of mathematical functions using the proposed method to show the advantages of the FDE algorithm.