A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems With Large-Scale Variables

State-of-the-art multiobjective evolutionary algorithms (MOEAs) treat all the decision variables as a whole to optimize performance. Inspired by the cooperative coevolution and linkage learning methods in the field of single objective optimization, it is interesting to decompose a difficult high-dim...

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Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 20; H. 2; S. 275 - 298
Hauptverfasser:	Ma, Xiaoliang, Liu, Fang, Qi, Yutao, Wang, Xiaodong, Li, Lingling, Jiao, Licheng, Yin, Minglei, Gong, Maoguo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Buildings cooperative co-evolution Couplings Decision analysis Decomposition Economic models Evolutionary algorithms Evolutionary computation Genetic algorithms Interacting variables Linear programming Linkages Mathematical analysis Mathematical models Mopping Optimization problem decomposition Variables multiobjective optimization decision variable analysis (DVA) interacting variables problem decomposition Cooperative coevolution
ISSN:	1089-778X, 1941-0026
Online-Zugang:	Volltext
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