Distributed and Asynchronous Algorithms for N-block Convex Optimization with Coupling Constraints
Optimization and Control
2021-03-26 v1
Abstract
This paper first proposes an N-block PCPM algorithm to solve N-block convex optimization problems with both linear and nonlinear constraints, with global convergence established. A linear convergence rate under the strong second-order conditions for optimality is observed in the numerical experiments. Next, for a starting point, an asynchronous N-block PCPM algorithm is proposed to solve linearly constrained N-block convex optimization problems. The numerical results demonstrate the sub-linear convergence rate under the bounded delay assumption, as well as the faster convergence with more short-time iterations than a synchronous iterative scheme.
Cite
@article{arxiv.2103.13560,
title = {Distributed and Asynchronous Algorithms for N-block Convex Optimization with Coupling Constraints},
author = {Run Chen and Andrew L. Liu},
journal= {arXiv preprint arXiv:2103.13560},
year = {2021}
}