MaOSSA: A new high-efficiency many-objective salp swarm algorithm with information feedback mechanism for industrial engineering problems

The pursuit of convergence in multi-objective optimization usually results in population clustering that produces suboptimal outcomes for both convergence and diversity performance. This paper introduces MaOSSA as a new Many-Objective Salp Swarm Algorithm which combines reference point strategies wi...

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Autori principali:	Mohammad Aljaidi, Janjhyam Venkata Naga Ramesh, Ajmeera Kiran, Pradeep Jangir, Arpita, Sundaram B. Pandya, Wulfran Fendzi Mbasso, Laith Abualigah, Ali Fayez Alkoradees, Mohammad Khishe
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2025-03-01
Serie:	Results in Engineering
Soggetti:	Multi-objective optimization Many-objective optimization Many-objective salp swarm algorithm Reference point Engineering design problems
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2590123025004529
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