On diagonally-preconditioning the 2-step BFGS method with accumulated steps for linearly constrained nonlinear programming

DOI10.1016/0377-2217(84)90192-9zbMath0544.90090OpenAlexW2060411610MaRDI QIDQ797502

Laureano Fernando Escudero Bueno

Publication date: 1984

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(84)90192-9

zbMATH Keywords

preconditioningde-activating strategieslarge-scale linearly constrained nonlinear programmingLimited-Storage Quasi-newton method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)

Uses Software

• L-BFGS

Cites Work

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• On diagonally preconditioning the truncated Newton method for super-scale linearly constrained nonlinear prrogramming
• An effective algorithm for minimization
• Solving systems of sparse linear equations
• QN-like variable storage conjugate gradients
• A Relationship between the BFGS and Conjugate Gradient Algorithms and Its Implications for New Algorithms
• Updating Quasi-Newton Matrices with Limited Storage
• Conjugate gradient methods for linearly constrained nonlinear programming
• Conjugate direction methods with variable storage
• Matrix conditioning and nonlinear optimization
• Large-scale linearly constrained optimization
• Conjugate Gradient Methods with Inexact Searches
• Convergence Conditions for Ascent Methods
• Quasi-Newton Methods for Unconstrained Optimization

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