Enhancing Metaheuristic Algorithm Performance Through Structured Population and Evolutionary Game Theory

Diversity is crucial for metaheuristic algorithms. It prevents early convergence, balances exploration and exploitation, and helps to avoid local optima. Traditional metaheuristic algorithms tend to rely on a single strategy for generating new solutions, often resulting in a lack of diversity. In co...

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Detalles Bibliográficos

Autores principales:	Héctor Escobar-Cuevas, Erik Cuevas, Alberto Luque-Chang, Oscar Barba-Toscano, Marco Pérez-Cisneros
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-11-01
Colección:	Mathematics
Materias:	metaheuristic game theory optimization competition Metropolis–Hastings
Acceso en línea:	https://www.mdpi.com/2227-7390/12/23/3676
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