A limited memory \(q\)-BFGS algorithm for unconstrained optimization problems

DOI10.1007/s12190-020-01432-6zbMath1475.65040OpenAlexW3084041523MaRDI QIDQ2053210

Geetanjali Panda, Suvra Kanti Chakraborty, Bhagwat Ram, Mohammad Esmael Samei, Kin Keung Lai, Shashi Kant Mishra

Publication date: 29 November 2021

Published in: Journal of Applied Mathematics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s12190-020-01432-6

zbMATH Keywords

unconstrained optimizationlarge-scale optimizationquasi-Newton methodlimited memory BFGS method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)

Related Items (5)

On \(q\)-BFGS algorithm for unconstrained optimization problems ⋮ Time accurate solution to Benjamin-Bona-Mahony-Burgers equation via Taylor-Boubaker series scheme ⋮ The strict complementarity in linear fractional optimization ⋮ Modified globally convergent Polak-Ribière-Polyak conjugate gradient methods with self-correcting property for large-scale unconstrained optimization ⋮ A \(q\)-Polak-Ribière-Polyak conjugate gradient algorithm for unconstrained optimization problems

Uses Software

• L-BFGS
• tn

Cites Work

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