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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
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Key Points
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.
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Gu et al. (Tue,) studied this question.
synapsesocial.com/papers/69a761b2c6e9836116a2fc04
https://doi.org/https://doi.org/10.1007/s12530-025-09787-6
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