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Main Authors: Sun, Xiangkai, Guo, Feng, He, Liang, Guo, Xiaole
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.29124
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author Sun, Xiangkai
Guo, Feng
He, Liang
Guo, Xiaole
author_facet Sun, Xiangkai
Guo, Feng
He, Liang
Guo, Xiaole
contents This paper deals with a new Tikhonov regularized primal-dual dynamical system with variable mass and Hessian-driven damping for solving a convex optimization problem with linear equality constraints. The system features several time-dependent parameters: variable mass, slow viscous damping, extrapolation, and temporal scaling. By employing the Lyapunov analysis approach, we obtain the strong convergence of the trajectory generated by the proposed system to the minimal norm solution of the optimization problem, as well as convergence rate results for the primal-dual gap, the objective residual, and the feasibility violation. We also show that the convergence rates of the primal-dual gap, the objective residual, and the feasibility violation can be improved by appropriately adjusting these parameters. Further, we conduct numerical experiments to demonstrate the effectiveness of the theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2603_29124
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Primal-dual dynamics featuring Hessian-driven damping and variable mass for convex optimization problems
Sun, Xiangkai
Guo, Feng
He, Liang
Guo, Xiaole
Optimization and Control
This paper deals with a new Tikhonov regularized primal-dual dynamical system with variable mass and Hessian-driven damping for solving a convex optimization problem with linear equality constraints. The system features several time-dependent parameters: variable mass, slow viscous damping, extrapolation, and temporal scaling. By employing the Lyapunov analysis approach, we obtain the strong convergence of the trajectory generated by the proposed system to the minimal norm solution of the optimization problem, as well as convergence rate results for the primal-dual gap, the objective residual, and the feasibility violation. We also show that the convergence rates of the primal-dual gap, the objective residual, and the feasibility violation can be improved by appropriately adjusting these parameters. Further, we conduct numerical experiments to demonstrate the effectiveness of the theoretical results.
title Primal-dual dynamics featuring Hessian-driven damping and variable mass for convex optimization problems
topic Optimization and Control
url https://arxiv.org/abs/2603.29124