Properties of the block BFGS update and its application to the limited-memory block BNS method for unconstrained minimization

DOI10.1007/s11075-018-0513-3zbMath1440.90076OpenAlexW2796081862WikidataQ130029069 ScholiaQ130029069MaRDI QIDQ670492

Jan Vlček, Ladislav Lukšan

Publication date: 18 March 2019

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11075-018-0513-3

zbMATH Keywords

algorithmsunconstrained optimizationglobal convergencenumerical experimentsBFGS updatelarge-scale problemslimited-memory methodsblock variable metric methodsBNS methodquasi-Newton conditions

Mathematics Subject Classification ID

Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Newton-type methods (49M15) Methods of quasi-Newton type (90C53)

Related Items (2)

Estimation of regional transition probabilities for spatial dynamic microsimulations from survey data lacking in regional detail ⋮ Two limited-memory optimization methods with minimum violation of the previous secant conditions

Uses Software

• L-BFGS
• CUTEr
• UFO
• CUTE
• LSA

Cites Work

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• 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 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
• Least Change Secant Updates for Quasi-Newton Methods
• Updating Quasi-Newton Matrices with Limited Storage
• Numerical Optimization
• CUTE
• Benchmarking optimization software with performance profiles.

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