Coevolutionary Multiobjective Evolutionary Algorithms: Survey of the State-of-the-Art

In the last 20 years, evolutionary algorithms (EAs) have shown to be an effective method to solve multiobjective optimization problems (MOPs). Due to their population-based nature, multiobjective EAs (MOEAs) are able to generate a set of tradeoff solutions (called nondominated solutions) in a single...

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Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 22; H. 6; S. 851 - 865
Hauptverfasser:	Miguel Antonio, Luis, Coello Coello, Carlos A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Coevolutionary algorithms (CAs) competitive coevolution Computer science cooperative coevolution (CC) Evolutionary algorithms Evolutionary computation Formulations Genetic algorithms Global optimization Mathematical analysis Mathematical programming Mopping multiobjective optimization Multiple objective analysis Pareto optimization Sociology Taxonomy
ISSN:	1089-778X, 1941-0026
Online-Zugang:	Volltext
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