A Multi-population QUasi-Affine TRansformation Evolution Algorithm for Global Optimization - Details

author：

Liu, Nengxian (Liu, Nengxian.) ^[1] | Pan, Jeng-Shyang (Pan, Jeng-Shyang.) ^[2] | Liao, Xiangwen (Liao, Xiangwen.) ^[3] (Scholars：廖祥文) | Chen, Guolong (Chen, Guolong.) ^[4] (Scholars：陈国龙)

Indexed by：

EI Scopus

Abstract：

In　this　paper,　we　propose　a　new　Multi-Population　QUasi-Affine　TRansformation　Evolution　(MP-QUATRE)　algorithm　for　global　optimization.　The　proposed　MP-QUATRE　algorithm　divides　the　population　into　three　sub-populations　with　a　sort　strategy　to　maintain　population　diversities,　and　each　sub-population　adopts　a　different　mutation　scheme　to　make　a　good　balance　between　exploration　and　exploitation　capability.　In　the　experiments,　we　compare　the　proposed　algorithm　with　DE　algorithm　and　QUATRE　algorithm　on　CEC2013　test　suite　for　real-parameter　optimization.　The　experimental　results　indicate　that　the　proposed　MP-QUATRE　algorithm　has　a　better　performance　than　the　competing　algorithms.　©　2019,　Springer　Nature　Singapore　Pte　Ltd.

Keyword：

Genetic algorithms Global optimization

Community：

[ 1 ] [Liu, Nengxian]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
[ 2 ] [Pan, Jeng-Shyang]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
[ 3 ] [Pan, Jeng-Shyang]Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China
[ 4 ] [Liao, Xiangwen]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
[ 5 ] [Chen, Guolong]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

Reprint 's Address：

潘正祥
[pan, jeng-shyang]college of mathematics and computer science, fuzhou university, fuzhou, china;;[pan, jeng-shyang]fujian provincial key lab of big data mining and applications, fujian university of technology, fuzhou, china

Email：

jspan@cc.kuas.edu.tw

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