Evolutionary Algorithm with Dynamic Population Size for Constrained Multiobjective Optimization

The core task of constrained multiobjective optimization is to achieve a tradeoff between exploration and exploitation as well as a tradeoff between constraints and objectives. We present an effective evolutionary algorithm with a dynamic population size (DPSEA) to achieve these two tradeoffs. In or...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 73; S. 101104
Hauptverfasser:	Wang, Bing-Chuan, Shui, Zhong-Yi, Feng, Yun, Ma, Zhongwei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.08.2022
Schlagworte:	Constrained multiobjective optimization dynamic population size evolutionary algorithm mating selection two tradeoffs Constrained multiobjective optimization dynamic population size two tradeoffs mating selection evolutionary algorithm
ISSN:	2210-6502
Online-Zugang:	Volltext
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