Distributed convex optimization based on ADMM and belief propagation methods

Title: Distributed convex optimization based on ADMM and belief propagation methods
Creator: Ma, Wenlong; Zhang, Huanshui; Fu, Minyue
Relation: Asian Journal of Control Vol. 23, Issue 2, p. 1040-1051
Publisher Link: http://dx.doi.org/10.1002/asjc.2284
Publisher: Wiley-Blackwell
Resource Type: journal article
Date: 2020
Description: We consider a distributed convex optimization problem in which a connected network of agents collaboratively seeks to minimize the sum of their local objective functions over a common decision variable. We propose a new distributed optimization method in the Alternating Direction Method of Multipliers (ADMM) framework, But our method combines the celebrated Belief Propagation(BP) algorithm and relaxation iteration method to achieve distributed optimization. Numerical simulation shows that our proposed algorithms have good convergence speed. We also discuss the trade-off between the convergence rate and the required communication and computational complexities.
Subject: alternating direction method of multipliers; belief propagation; distributed optimization; relaxation iteration method
Identifier: http://hdl.handle.net/1959.13/1435687
Identifier: uon:39787
Identifier: ISSN:1561-8625
Language: eng
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