A Duality-Based Approach for Distributed Optimization with Coupling Constraints
Systems and Control
2018-04-25 v1
Abstract
In this paper we consider a distributed optimization scenario in which a set of agents has to solve a convex optimization problem with separable cost function, local constraint sets and a coupling inequality constraint. We propose a novel distributed algorithm based on a relaxation of the primal problem and an elegant exploration of duality theory. Despite its complex derivation based on several duality steps, the distributed algorithm has a very simple and intuitive structure. That is, each node solves a local version of the original problem relaxation, and updates suitable dual variables. We prove the algorithm correctness and show its effectiveness via numerical computations.
Cite
@article{arxiv.1804.09105,
title = {A Duality-Based Approach for Distributed Optimization with Coupling Constraints},
author = {Ivano Notarnicola and Giuseppe Notarstefano},
journal= {arXiv preprint arXiv:1804.09105},
year = {2018}
}