caa a22 4500 605470820 CHVBK 20210128100330.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00500-014-1482-7 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1482-7 Heterozygous differential evolution with Taguchi local search [Elektronische Daten] [Hu Peng, Zhijian Wu] Differential evolution (DE) is one of the most popular and powerful evolutionary algorithms for the real-parameter global continuous optimization problems. However, how to balance the exploration and exploitation is harder work to the researchers improving the performance of DE. Very often, we catch one and lose another. To overcome this problem, this paper presents a novel DE variant, called heterozygous DE with Taguchi local search (THDE), in which two new proposed methods (i.e., multiple schemes heterozygous evolution and Taguchi local search) are employed, with one as enhanced exploration ability and the other enhanced exploitation ability. The experimental studies have been conducted on 27 well-known test functions, including unimodal, multimodal and shifted test functions. Experimental results have verified the quality and effectiveness of THDE. Comparison with the state-of-the-art DE variants has proved that THDE is a type of new competitive algorithm. Springer-Verlag Berlin Heidelberg, 2014 Differential evolution nationallicence Global optimization nationallicence Heterozygous evolution nationallicence Taguchi local search nationallicence Peng Hu State Key Lab of Software Engineering, School of Computer, Wuhan University, 430072, Wuhan, China aut Wu Zhijian State Key Lab of Software Engineering, School of Computer, Wuhan University, 430072, Wuhan, China aut Soft Computing Springer Berlin Heidelberg 19/11(2015-11-01), 3273-3291 1432-7643 19:11<3273 2015 19 500 https://doi.org/10.1007/s00500-014-1482-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1482-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Peng Hu State Key Lab of Software Engineering, School of Computer, Wuhan University, 430072, Wuhan, China aut NATIONALLICENCE 700 1- Wu Zhijian State Key Lab of Software Engineering, School of Computer, Wuhan University, 430072, Wuhan, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/11(2015-11-01), 3273-3291 1432-7643 19:11<3273 2015 19 500