Multi-Strategy-Improvement-Based Slime Mould Algorithm

In addressing the challenges posed by the sluggish convergence rate, suboptimal stability, and susceptibility to local optimization in function optimization problems, a multi-strategy-based enhanced slime mold optimization algorithm (MSSMA) has been proposed. This algorithm integrates chaotic mappin...

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Auteurs principaux:	Donghai Huang, Tianbing Tang, Yi Yan
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2025-05-01
Collection:	Applied Sciences
Sujets:	slime mould algorithm chaotic mapping inverse learning elite tangent search
Accès en ligne:	https://www.mdpi.com/2076-3417/15/10/5456
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