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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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Hauptverfasser: Héctor Escobar-Cuevas, Erik Cuevas, Alberto Luque-Chang, Oscar Barba-Toscano, Marco Pérez-Cisneros
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2024-11-01
Schriftenreihe:Mathematics
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Online-Zugang:https://www.mdpi.com/2227-7390/12/23/3676
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