Differential evolution with controlled search direction
来源期刊：中南大学学报(英文版)2012年第12期
论文作者：JIA Li-yuan (贾丽媛) HE Jian-xin (何建新) ZHANG Chi (张弛) GONG Wen-yin (龚文引)
文章页码：3516 - 3523
Key words：differential evolution; evolutionary algorithm; search direction; numerical optimization
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.
JIA Li-yuan (贾丽媛)1, HE Jian-xin (何建新)2, ZHANG Chi (张弛)1, GONG Wen-yin (龚文引)2
(1. Department of Computer Science, Hunan City University, Yiyang 413000, China;
2. School of Computer Science, China University of Geosciences, Wuhan 430074, China)
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.
Key words:differential evolution; evolutionary algorithm; search direction; numerical optimization
