A two-stage accelerated search strategy for large-scale multi-objective evolutionary algorithm

Since large-scale multi-objective problems (LSMOPs) have huge decision variables, the traditional evolutionary algorithms are facing difficulties of low exploitation efficiency and high exploration costs in solving LSMOPs. Therefore, this paper proposes an evolutionary strategy based on two-stage ac...

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Vydáno v:	Information sciences Ročník 686; s. 121347
Hlavní autoři:	Cui, Zhihua, Wu, Yijing, Zhao, Tianhao, Zhang, Wensheng, Chen, Jinjun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Inc 01.01.2025
Témata:	Accelerated search Artificial neural network Evolutionary algorithm Large-scale multi-objective optimization algorithm Opposite learning Accelerated search Large-scale multi-objective optimization algorithm Artificial neural network Opposite learning Evolutionary algorithm
ISSN:	0020-0255
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