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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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Principais autores: Héctor Escobar-Cuevas, Erik Cuevas, Alberto Luque-Chang, Oscar Barba-Toscano, Marco Pérez-Cisneros
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-11-01
Serier:Mathematics
Fag:
metaheuristic
game theory
optimization
competition
Metropolis–Hastings
Online adgang:https://www.mdpi.com/2227-7390/12/23/3676
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