Primal-Dual Method for Optimization Problems with Changing Constraints
Optimization and Control
2022-01-04 v1 Distributed, Parallel, and Cluster Computing
Multiagent Systems
Abstract
We propose a modified primal-dual method for general convex optimization problems with changing constraints. We obtain properties of Lagrangian saddle points for these problems which enable us to establish convergence of the proposed method. We describe specializations of the proposed approach to multi-agent optimization problems under changing communication topology and to feasibility problems.
Cite
@article{arxiv.2201.00334,
title = {Primal-Dual Method for Optimization Problems with Changing Constraints},
author = {Igor Konnov},
journal= {arXiv preprint arXiv:2201.00334},
year = {2022}
}
Comments
15 pages