A coevolutionary constrained multi-objective algorithm with a learning constraint boundary

When solving constrained multi-objective optimization problems, the balance of convergence, diversity, and feasibility plays a pivotal role. To address this issue, this paper proposes a coevolutionary constrained multi-objective algorithm with learning constraint boundary (CCMOLCB). Firstly, the con...

Celý popis

Podrobná bibliografie

Vydáno v:	Applied soft computing Ročník 148; s. 110845
Hlavní autoři:	Cao, Jie, Yan, Zesen, Chen, Zuohan, Zhang, Jianlin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.11.2023
Témata:	Constrained multi-objective evolutionary algorithms Constrained multi-objective optimization Multiple-populations Constrained multi-objective optimization Multiple-populations Constrained multi-objective evolutionary algorithms
ISSN:	1568-4946, 1872-9681
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!