{"ID":2856438,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.11554","arxiv_id":"2510.11554","title":"An Efficient Solution Method for Solving Convex Separable Quadratic Optimization Problems","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.","short_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 cons...","url_abs":"https://arxiv.org/abs/2510.11554","url_pdf":"https://arxiv.org/pdf/2510.11554v1","authors":"[\"Shaoze Li\",\"Junhao Wu\",\"Cheng Lu\",\"Zhibin Deng\",\"Shu-Cherng Fang\"]","published":"2025-10-13T15:54:55Z","proceeding":"math.OC","tasks":"[\"math.OC\"]","methods":"[]","has_code":false}