A novel three-stage multi-population evolutionary algorithm for constrained multi-objective optimization problems

Lots of real-world optimization problems are inherently constrained multi-objective optimization problems (CMOPs), but the existing constrained multi-objective optimization evolutionary algorithms (CMOEAs) often fail to balance convergence and diversity effectively. Therefore, a novel constrained mu...

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Vydané v:	Complex & intelligent systems Ročník 10; číslo 1; s. 655 - 675
Hlavní autori:	Shi, Chenli, Wang, Ziqi, Jin, Xiaohang, Xu, Zhengguo, Wang, Zhangsheng, Shen, Peng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.02.2024 Springer Nature B.V Springer
Predmet:	Coevolution Complexity Computational Intelligence Constrained multi-objective optimization problems (CMOPs) Constraints Convergence Data Structures and Information Theory Engineering Evolutionary algorithms Genetic algorithms Multiple objective analysis Optimization Original Article Parallel algorithm Pareto optimization Search process Staging strategy Constrained multi-objective optimization problems (CMOPs) Parallel algorithm Evolutionary algorithms Staging strategy Coevolution
ISSN:	2199-4536, 2198-6053
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