Saved in:
Bibliographic Details
Main Authors: Jin, Jiachen, Wang, Hongxia, Deng, Kangkang
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.14924
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912838873776128
author Jin, Jiachen
Wang, Hongxia
Deng, Kangkang
author_facet Jin, Jiachen
Wang, Hongxia
Deng, Kangkang
contents The derivative-free projection method (DFPM) is an efficient algorithm for solving monotone nonlinear equations. As problems grow larger, there is a strong demand for speeding up the convergence of DFPM. This paper considers the application of Anderson acceleration (AA) to DFPM for constrained monotone nonlinear equations. By employing a nonstationary relaxation parameter and interleaving with slight modifications in each iteration, a globally convergent variant of AA for DFPM named as AA-DFPM is proposed. Further, the linear convergence rate is proved under some mild assumptions. Experiments on both mathematical examples and a real-world application show encouraging results of AA-DFPM and confirm the suitability of AA for accelerating DFPM in solving optimization problems.
format Preprint
id arxiv_https___arxiv_org_abs_2403_14924
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Anderson acceleration of derivative-free projection methods for constrained monotone nonlinear equations
Jin, Jiachen
Wang, Hongxia
Deng, Kangkang
Optimization and Control
The derivative-free projection method (DFPM) is an efficient algorithm for solving monotone nonlinear equations. As problems grow larger, there is a strong demand for speeding up the convergence of DFPM. This paper considers the application of Anderson acceleration (AA) to DFPM for constrained monotone nonlinear equations. By employing a nonstationary relaxation parameter and interleaving with slight modifications in each iteration, a globally convergent variant of AA for DFPM named as AA-DFPM is proposed. Further, the linear convergence rate is proved under some mild assumptions. Experiments on both mathematical examples and a real-world application show encouraging results of AA-DFPM and confirm the suitability of AA for accelerating DFPM in solving optimization problems.
title Anderson acceleration of derivative-free projection methods for constrained monotone nonlinear equations
topic Optimization and Control
url https://arxiv.org/abs/2403.14924