Global convergence of a descent PRP type conjugate gradient method for nonconvex optimization

DOI10.1016/j.apnum.2021.11.001zbMath1484.65122OpenAlexW3214140244MaRDI QIDQ2073942

Yu Chen, Hongrun Zhang, Qing-Jie Hu

Publication date: 3 February 2022

Published in: Applied Numerical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apnum.2021.11.001

zbMATH Keywords

global convergenceWolfe line searchArmijo line searchsufficient descent conditionnonconvex unconstrained optimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Methods of reduced gradient type (90C52)

Related Items (4)

A truncated three-term conjugate gradient method with complexity guarantees with applications to nonconvex regression problem ⋮ A modified PRP-type conjugate gradient algorithm with complexity analysis and its application to image restoration problems ⋮ A new three-term spectral subgradient method for solving absolute value equation ⋮ An efficient conjugate gradient-based algorithm for unconstrained optimization and its projection extension to large-scale constrained nonlinear equations with applications in signal recovery and image denoising problems

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