Title: An improved differential evolution algorithm based on suboptimal solution mutation

Authors: Liang Chen; Chong Zhou; Xiangping Li; Guangming Dai

Addresses: School of Computer, China University of Geosciences, Wuhan, 430074, China ' School of Computer, China University of Geosciences, Wuhan, 430074, China ' School of Computer, China University of Geosciences, Wuhan, 430074, China ' School of Computer, China University of Geosciences, Wuhan, 430074, China

Abstract: In order to improve the drawbacks of DE algorithm with DE/best/1 such as the rapid convergence speed and local optimum, this paper proposes an improved DE algorithm. Based on the DE/best/1 mutation operator, a new mutation operator is constructed. The best M individuals are summed as a new individual to replace the base individual of the DE/best/1. This is helpful to avoid falling into local optimum for the fast convergence. Simulation experiments demonstrate that the proposed algorithm outperforms some standard DE variants.

Keywords: differential evolution; mutation operator; global optimisation; function optimisation; suboptimal solution mutation; simulation.

DOI: 10.1504/IJCSM.2017.083141

International Journal of Computing Science and Mathematics, 2017 Vol.8 No.1, pp.28 - 34

Received: 10 Jun 2016
Accepted: 12 Jul 2016
Published online: 21 Mar 2017 *

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