A subspace conjugate gradient algorithm for large-scale unconstrained optimization

DOI10.1007/s11075-017-0284-2zbMath1379.65038OpenAlexW2586727428MaRDI QIDQ1681785

Yunlong Lu, Yue-Ting Yang, Yu-Ting Chen

Publication date: 24 November 2017

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

Full work available at URL: https://doi.org/10.1007/s11075-017-0284-2

zbMATH Keywords

numerical exampleglobal convergenceconjugate gradient methodWolfe line searchlarge-scale unconstrained optimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30)

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A new subspace minimization conjugate gradient method based on tensor model for unconstrained optimization ⋮ A new subspace minimization conjugate gradient method with nonmonotone line search for unconstrained optimization ⋮ A regularized limited memory subspace minimization conjugate gradient method for unconstrained optimization ⋮ A new subspace minimization conjugate gradient method for unconstrained minimization ⋮ An efficient Barzilai-Borwein conjugate gradient method for unconstrained optimization ⋮ A class of accelerated subspace minimization conjugate gradient methods ⋮ New subspace minimization conjugate gradient methods based on regularization model for unconstrained optimization ⋮ Two families of scaled three-term conjugate gradient methods with sufficient descent property for nonconvex optimization ⋮ A new accelerated conjugate gradient method for large-scale unconstrained optimization ⋮ A subspace minimization conjugate gradient method based on conic model for unconstrained optimization ⋮ Several accelerated subspace minimization conjugate gradient methods based on regularization model and convergence rate analysis for nonconvex problems

Uses Software

• L-BFGS

Cites Work

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