{"ID":2837807,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.19708","arxiv_id":"2511.19708","title":"An Accelerated Distributed Optimization with Equality and Inequality Coupling Constraints","abstract":"This paper studies distributed convex optimization with both affine equality and nonlinear inequality couplings through the duality analysis. We first formulate the dual of the coupling-constraint problem and reformulate it as a consensus optimization problem over a connected network. To efficiently solve this dual problem and hence the primal problem, we design an accelerated linearized algorithm that, at each round, a look-ahead linearization of the separable objective is combined with a quadratic penalty on the Laplacian constraint, a proximal step, and an aggregation of iterations. On the theory side, we prove non-ergodic rates for both the primal optimality error and the feasibility error. On the other hand, numerical experiments show a faster decrease of optimality error and feasibility residual than augmented-Lagrangian tracking and distributed subgradient baselines under the same communication budget.","short_abstract":"This paper studies distributed convex optimization with both affine equality and nonlinear inequality couplings through the duality analysis. We first formulate the dual of the coupling-constraint problem and reformulate it as a consensus optimization problem over a connected network. To efficiently solve this dual pro...","url_abs":"https://arxiv.org/abs/2511.19708","url_pdf":"https://arxiv.org/pdf/2511.19708v2","authors":"[\"Chenyang Qiu\",\"Yangyang Qian\",\"Zongli Lin\",\"Yacov A. Shamash\"]","published":"2025-11-24T21:17:41Z","proceeding":"math.OC","tasks":"[\"math.OC\",\"eess.SY\"]","methods":"[]","has_code":false}