Review of coevolutionary developments of evolutionary multi-objective and many-objective algorithms and test problems

In the evolutionary multi-objective optimization (EMO) community, some well-known test problems have been frequently and repeatedly used to evaluate the performance of EMO algorithms. When a new EMO algorithm is proposed, its performance is evaluated on those test problems. Thus algorithm developmen...

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Vydané v:	2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) s. 178 - 184
Hlavní autori:	Ishibuchi, Hisao, Masuda, Hiroyuki, Tanigaki, Yuki, Nojima, Yusuke
Médium:	Konferenčný príspevok..
Jazyk:	English Japanese
Vydavateľské údaje:	IEEE 01.12.2014
Predmet:	Algorithm design and analysis Convergence diversity Evolutionary multi-objective optimization (EMO) Maintenance engineering many-objective optimization Pareto optimization Sociology
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