Inicio
Explorar
nav.journalClub
Tendencias
Más
synapse
⌘+K
Idioma
Español
Español
Fractional Newton-derived optimizer: a novel metaheuristic for global optimization problems | Synapse
March 3, 2026
Fractional Newton-derived optimizer: a novel metaheuristic for global optimization problems
YG
Yangyang Gu
YM
Yaqian Mao
YS
Yuqiu Shen
Ver todo
Puntos clave
Improved convergence properties observed using the fractional newton-derived optimizer, effectively enhancing solution finding in complex scenarios.
Performance metrics revealed an average improvement of 25% in solution quality across diverse optimization problems.
Application of the metaheuristic approach involves iteratively refining solutions, combining classical methods with novel techniques.
Highlights the need for further exploration of algorithm robustness across varied problem landscapes to ensure broad applicability.
Mark Helpful
Me gusta
Save
Guardar
Relay
Compartir
Cite This Study
Copy
Gu et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761b2c6e9836116a2fc04
https://doi.org/https://doi.org/10.1007/s12530-025-09787-6
Mark Helpful
Me gusta
Save
Guardar
Relay
Compartir