Self-Adaptive Limited-Memory Quasi-Newton Method with Function Value Information for Large-Scale Unconstrained Optimization

We extend the modified BFGS algorithm to a limited-memory framework, and propose a self-adaptive limited-memory quasi-Newton method, denoted as LADBFGS, for large-scale unconstrained optimization. The proposed method fully exploits function value information to improve the curvature approximation of...

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Detalles Bibliográficos

Principais autores:	Jiangwen Ju, Weixin Lin, Hao Liu
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2026-05-01
Series:	Mathematics
Assuntos:	unconstrained optimization quasi-Newton method limited-memory BFGS weak secant equation
Acceso en liña:	https://www.mdpi.com/2227-7390/14/10/1750
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