Differential evolution with controlled search direction

Abstract

A novel and simple technique to control the search direction of the differential mutation was proposed. In order to verify the performance of this method, ten widely used benchmark functions were chosen and the results were compared with the original differential evolution (DE) algorithm. Experimental results indicate that the search direction controlled DE algorithm obtains better results than the original DE algorithm in term of the solution quality and convergence rate.

Keywords

differential evolution / evolutionary algorithm / search direction / numerical optimization

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