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A new adaptive trust region algorithm for optimization problems

Published:2018-03 Issue:2 Volume:38 Page:479-496
ISSN:0252-9602
Container-title:Acta Mathematica Scientia
language:en
Short-container-title:Acta Mathematica Scientia

Author:

SHENG Zhou,YUAN Gonglin,CUI Zengru

Funder

National Natural Science Foundation of China

Guangxi Science Fund for Distinguished Young Scholars

Guangxi Natural Science Key Fund

Basic Ability Promotion Project of Guangxi Young and Middle-Aged Teachers

Publisher

Elsevier BV

Subject

General Physics and Astronomy,General Mathematics

Reference42 articles.

1. An adaptive conjugate gradient algorithm for lagre-scale unconstrained optimization;Andrei;J Comput Appl Math,2016

2. Modified nonlinear conjugate gradient methods with sufficient descent property for large-scale optimization problems;Yuan;Optim Lett,2009

3. A modified PRP conjugate gradient method;Yuan;Anna Operat Res,2009

4. A conjugate gradient method with descent direction for unconstrained optimization;Yuan Lu;J Comput Appl Math,2009

5. A modified Polak-Ribière-Polyak conjugate gradient algorithm for large-scale optimization problems;Yuan;IEEE Tran,2014

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1. Global convergence of a cautious projection BFGS algorithm for nonconvex problems without gradient Lipschitz continuity;Acta Mathematica Scientia;2024-08-27

2. Some convergently three-term trust region conjugate gradient algorithms under gradient function non-Lipschitz continuity;Scientific Reports;2024-05-13

3. A nonmonotone adaptive trust region technique with a forgetting factor;International Journal of Computer Mathematics;2024-05-03

4. Sub‐sampled adaptive trust region method on Riemannian manifolds;Numerical Linear Algebra with Applications;2024-04-13

5. Convergence and worst-case complexity of adaptive Riemannian trust-region methods for optimization on manifolds;Journal of Global Optimization;2024-03-18

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