Distributed Proximal Minimization Algorithm for Constrained Convex Optimization over Strongly Connected Networks

Naoki HAYASHI  Masaaki NAGAHARA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E102-A   No.2   pp.351-358
Publication Date: 2019/02/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E102.A.351
Type of Manuscript: Special Section PAPER (Special Section on Mathematical Systems Science and its Applications)
Category: 
Keyword: 
distributed optimization,  proximal minimization algorithm,  cooperative control,  multi-agent system,  

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Summary: 
This paper proposes a novel distributed proximal minimization algorithm for constrained optimization problems over fixed strongly connected networks. At each iteration, each agent updates its own state by evaluating a proximal operator of its objective function under a constraint set and compensating the unbalancing due to unidirectional communications. We show that the states of all agents asymptotically converge to one of the optimal solutions. Numerical results are shown to confirm the validity of the proposed method.