An Efficient Solution Method for Solving Convex Separable Quadratic Optimization Problems
Optimization and Control
2025-10-14 v1
Abstract
Convex separable quadratic optimization problems occur in many practical applications. In this paper, based on an iterative resolution scheme of the KKT system, we develop an efficient method for solving a quadratic programming problem with a convex separable objective function subject to multiple convex separable constraints. We show that the proposed approach leads to a dual coordinate ascent algorithm and provide a convergence proof. Numerical experiments support the superior performance of the proposed method to that of the Gurobi solver, especially for solving large-scale convex separate quadratic programming problems.
Cite
@article{arxiv.2510.11554,
title = {An Efficient Solution Method for Solving Convex Separable Quadratic Optimization Problems},
author = {Shaoze Li and Junhao Wu and Cheng Lu and Zhibin Deng and Shu-Cherng Fang},
journal= {arXiv preprint arXiv:2510.11554},
year = {2025}
}