DocumentCode
3751504
Title
A Gene-Level Hybrid Crossover Operator for Multiobjective Evolutionary Algorithm
Author
Qingling Zhu;Qiuzhen Lin;Jianyong Chen;Peizhi Huang
Author_Institution
Coll. of Comput. Sci. &
fYear
2015
Firstpage
20
Lastpage
24
Abstract
This study proposes a novel recombination operator, called hybrid crossover operator (HX), which is performed in gene level of chromosome to enhance the optimization performance of multi-objective evolutionary algorithms (MOEAs). The proposed HX operator combines the advantages of simulated binary crossover with local search ability and differential evolution with strong global search capability. When HX is embedded into two state-of-the-art MOEAs, i.e., NSGA-II and MOEA/D-DE, the experimental results validate the improvement of HX when compared to the original counterpart.
Keywords
"Biological cells","Optimization","Sociology","Statistics","Diversity reception","Evolutionary computation","Search problems"
Publisher
ieee
Conference_Titel
Soft Computing and Machine Intelligence (ISCMI), 2015 Second International Conference on
Type
conf
DOI
10.1109/ISCMI.2015.25
Filename
7414666
Link To Document