| Issue |
RAIRO-Oper. Res.
Volume 59, Number 5, September-October 2025
|
|
|---|---|---|
| Page(s) | 2437 - 2449 | |
| DOI | https://doi.org/10.1051/ro/2025106 | |
| Published online | 05 September 2025 | |
A subspace minimization conjugate gradient method for nonlinear monotone equations with convex constraints
1
College of Mathematics and Statistics, Chongqing Three Gorges University, Chongqing 404100, P.R. China
2
School of Mathematical and Physical Sciences, Chongqing University of Science and Technology, Chongqing 401331, P.R. China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
4
August
2024
Accepted:
21
July
2025
The subspace minimization conjugate gradient method is currently one of the popular optimization methods. Based on this method and the projection technique, in this paper we propose a three-term subspace minimization conjugate gradient method for solving large-scale nonlinear monotone equations with convex constraints. The search direction is obtained by minimizing the quadratic approximate function in a three-dimensional subspace, and satisfies the sufficient descent condition. The global convergence of the proposed algorithm is proved under some appropriate conditions. Numerical results indicate the effectiveness of the proposed algorithm.
Mathematics Subject Classification: 90C30 / 90C06 / 65K05 / 65K10
Key words: Nonlinear equations / subspace minimization conjugate gradient method / projection technique / global convergence
© The authors. Published by EDP Sciences, ROADEF, SMAI 2025
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