An accelerated primal-dual flow for linearly constrained multiobjective optimization

Fuente: arXiv
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Main Authors: Luo, Hao, Shu, Qiaoyuan, Yang, Xinmin
Format: Preprint
Published: 2025
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_version_ 1866908629233303552
author Luo, Hao
Shu, Qiaoyuan
Yang, Xinmin
author_facet Luo, Hao
Shu, Qiaoyuan
Yang, Xinmin
contents In this paper, we propose a continuous-time primal-dual approach for linearly constrained multiobjective optimization problems. A novel dynamical model, called accelerated multiobjective primal-dual flow, is presented with a second-order equation for the primal variable and a first-order equation for the dual variable. It can be viewed as an extension of the accelerated primal-dual flow by Luo [arXiv:2109.12604, 2021] for the single objective case. To facilitate the convergence rate analysis, we introduce a new merit function, which motivates the use of the feasibility violation and the objective gap to measure the weakly Pareto optimality. By using a proper Lyapunov function, we establish the exponential decay rate in the continuous level. After that, we consider an implicit-explicit scheme, which yields an accelerated multiobjective primal-dual method with a quadratic subproblem, and prove the sublinear rates of the feasibility violation and the objective gap, under the convex case and the strongly convex case, respectively. Numerical results are provided to demonstrate the performance of the proposed method.
format Preprint
id arxiv_https___arxiv_org_abs_2511_02751
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An accelerated primal-dual flow for linearly constrained multiobjective optimization
Luo, Hao
Shu, Qiaoyuan
Yang, Xinmin
Optimization and Control
Numerical Analysis
90C29, 90C30
In this paper, we propose a continuous-time primal-dual approach for linearly constrained multiobjective optimization problems. A novel dynamical model, called accelerated multiobjective primal-dual flow, is presented with a second-order equation for the primal variable and a first-order equation for the dual variable. It can be viewed as an extension of the accelerated primal-dual flow by Luo [arXiv:2109.12604, 2021] for the single objective case. To facilitate the convergence rate analysis, we introduce a new merit function, which motivates the use of the feasibility violation and the objective gap to measure the weakly Pareto optimality. By using a proper Lyapunov function, we establish the exponential decay rate in the continuous level. After that, we consider an implicit-explicit scheme, which yields an accelerated multiobjective primal-dual method with a quadratic subproblem, and prove the sublinear rates of the feasibility violation and the objective gap, under the convex case and the strongly convex case, respectively. Numerical results are provided to demonstrate the performance of the proposed method.
title An accelerated primal-dual flow for linearly constrained multiobjective optimization
topic Optimization and Control
Numerical Analysis
90C29, 90C30
url https://arxiv.org/abs/2511.02751