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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 27; H. 2; S. 326 - 340
Hauptverfasser:	Deng, Qi, Kang, Qi, Zhang, Liang, Zhou, MengChu, An, Jing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!