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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Hlavní autoři:	Héctor Escobar-Cuevas, Erik Cuevas, Alberto Luque-Chang, Oscar Barba-Toscano, Marco Pérez-Cisneros
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-11-01
Edice:	Mathematics
Témata:	metaheuristic game theory optimization competition Metropolis–Hastings
On-line přístup:	https://www.mdpi.com/2227-7390/12/23/3676
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