Feature Extraction for Recommendation of Constrained Multiobjective Evolutionary Algorithms

The evolutionary algorithm recommendation is catching increasing attention when solving practical application problems since different algorithms often perform differently on different problems. To achieve the algorithm recommendation, extracting effective features to accurately characterize the pro...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 27; no. 4; pp. 949 - 963
Main Authors:	Qiao, Kangjia, Yu, Kunjie, Qu, Boyang, Liang, Jing, Yue, Caitong, Ban, Xuanxuan
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithm recommendation constrained multiobjective optimization Constraints Evolutionary algorithms Evolutionary computation Feature extraction Genetic algorithms Machine learning algorithms Mathematical analysis Multiple objective analysis Optimization Prediction algorithms Recommender systems Sociology Task analysis
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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