Enhanced mutation strategy for differential evolution

Abstract

It is well known that mutation plays a very important role in the successful performance of Differential Evolution (DE) algorithm. The proposed scheme named Modified Random Localization (MRL) is based on strategically selecting the individuals from the entire search space rather than choosing them randomly as in basic DE. The corresponding DE variant named MRL-DE is analyzed on a set of 8 traditional benchmark functions and 6 nontraditional shifted functions. Numerical and statistical results indicate the competence of the proposed MRL-DE for solving unconstrained global optimization problems.