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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Bibliographic Details

Published in:	Information sciences Vol. 686; p. 121347
Main Authors:	Cui, Zhihua, Wu, Yijing, Zhao, Tianhao, Zhang, Wensheng, Chen, Jinjun
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.01.2025
Subjects:	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
Online Access:	Get full text
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