Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes

Recently, a number of high performance many-objective evolutionary algorithms with systematically generated weight vectors have been proposed in the literature. Those algorithms often show surprisingly good performance on widely used DTLZ and WFG test problems. The performance of those algorithms ha...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 21; no. 2; pp. 169 - 190
Main Authors:	Ishibuchi, Hisao, Setoguchi, Yu, Masuda, Hiroyuki, Nojima, Yusuke
Format:	Journal Article
Language:	English
Published:	IEEE 01.04.2017
Subjects:	Convergence Decomposition-based evolutionary algorithms Evolutionary computation Maintenance engineering many-objective evolutionary algorithms many-objective optimization many-objective test problems Optimization Performance evaluation Search problems Shape
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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