Two limited-memory optimization methods with minimum violation of the previous secant conditions

DOI10.1007/s10589-021-00318-yzbMath1491.65044OpenAlexW3200672889MaRDI QIDQ2057221

Jan Vlček, Ladislav Lukšan

Publication date: 8 December 2021

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-021-00318-y

zbMATH Keywords

global convergencenumerical resultsvariable metric methodsunconstrained minimizationlimited-memory methodsvariationally derived methods

Mathematics Subject Classification ID

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

Uses Software

• L-BFGS
• CUTEr
• UFO
• CG_DESCENT
• CUTE
• LSA

Cites Work

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• Properties of the block BFGS update and its application to the limited-memory block BNS method for unconstrained minimization
• On the limited memory BFGS method for large scale optimization
• Representations of quasi-Newton matrices and their use in limited memory methods
• Variable metric methods for unconstrained optimization and nonlinear least squares
• A limited-memory optimization method using the infinitely many times repeated BNS update and conjugate directions
• The global convergence of a modified BFGS method for nonconvex functions
• A conjugate directions approach to improve the limited-memory BFGS method
• A modified limited-memory BNS method for unconstrained minimization based on the conjugate directions idea
• Algorithm 896
• Algorithm 851
• Least Change Secant Updates for Quasi-Newton Methods
• Updating Quasi-Newton Matrices with Limited Storage
• Numerical Optimization
• CUTE
• A modified BFGS method and its global convergence in nonconvex minimization
• Benchmarking optimization software with performance profiles.

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