Objective Space-Based Population Generation to Accelerate Evolutionary Algorithms for Large-Scale Many-Objective Optimization

The generation and updating of solutions, e.g., crossover and mutation, of many existing evolutionary algorithms directly operate on decision variables. The operators are very time consuming for large-scale and many-objective optimization problems. Different from them, this work proposes an objectiv...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 27; no. 2; pp. 326 - 340
Main Authors:	Deng, Qi, Kang, Qi, Zhang, Liang, Zhou, MengChu, An, Jing
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Approximation algorithms Convergence Decision variables decomposition Evolutionary algorithms Evolutionary computation Genetic algorithms Inverse problems large-scale evolution many-objective evolution Multiple objective analysis objective space mapping Optimization Sociology Statistics
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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