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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Bibliographic Details

Published in:	2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM) pp. 178 - 184
Main Authors:	Ishibuchi, Hisao, Masuda, Hiroyuki, Tanigaki, Yuki, Nojima, Yusuke
Format:	Conference Proceeding
Language:	English Japanese
Published:	IEEE 01.12.2014
Subjects:	Algorithm design and analysis Convergence diversity Evolutionary multi-objective optimization (EMO) Maintenance engineering many-objective optimization Pareto optimization Sociology
Online Access:	Get full text
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