DocumentCode
3593254
Title
Selection Strategies of Evolutionary Algorithms in Multiobjective Optimization
Author
Xie, C.W. ; Ding, L.X.
Author_Institution
State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China
Volume
4
fYear
2009
Firstpage
633
Lastpage
637
Abstract
The study on selection strategies of evolutionary algorithms in multiobjective optimization (MOEAs) is scarce.This paper mostly researches on various selection strategies of MOEAs. Firstly, the paper discusses how to construct an appropriate fitness function in multiobjective optimization problem, then, selection strategies are classified as six categories through systematically analyzing various MOEAs. To each selection strategy, we not only analyze its operation mechanism but also point out its advantages, weaknesses and applications. Although our study is not profound, it will be helpful to design more efficient MOEAs.
Keywords
evolutionary computation; evolutionary algorithms; multiobjective optimization; selection strategies; Algorithm design and analysis; Evolutionary computation; Laboratories; Software engineering; Sorting; Evolutionary Algorithm; Multiobjective Optimization; Selection Strategy;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.35
Filename
5363435
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