For Global Optimization Problems (GOPs), we propose a new variant of DE with linear neighborhood search, called LiNDE which employs a linear combination of triple vectors taken randomly from evolutionary population, in order to improve the ability of neighborhood search of Differential Evolutionary (DE) algorithm. The main characteristics of LiNDE are less parameters and powerful neighborhood search ability. Experimental studies are carried out on a benchmark set and the results show that LiNDE significantly improves the performance of DE. PDFFulltextXMLReferencesCitation
How to cite this article
Yuzhen Liu and Shoufu Li, 2011. A New Differential Evolutionary Algorithm with Neighborhood Search. Information Technology Journal, 10: 573-578.