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Distributed Constrained Convex Optimization with Accumulated Subgradient Information over Undirected Switching Networks

Yuichi KAJIYAMA, Naoki HAYASHI, Shigemasa TAKAI

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Summary :

This paper proposes a consensus-based subgradient method under a common constraint set with switching undirected graphs. In the proposed method, each agent has a state and an auxiliary variable as the estimates of an optimal solution and accumulated information of past gradients of neighbor agents. We show that the states of all agents asymptotically converge to one of the optimal solutions of the convex optimization problem. The simulation results show that the proposed consensus-based algorithm with accumulated subgradient information achieves faster convergence than the standard subgradient algorithm.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E102-A No.2 pp.343-350
Publication Date
2019/02/01
Publicized
Online ISSN
1745-1337
DOI
10.1587/transfun.E102.A.343
Type of Manuscript
Special Section PAPER (Special Section on Mathematical Systems Science and its Applications)
Category

Authors

Yuichi KAJIYAMA
  Osaka University
Naoki HAYASHI
  Osaka University
Shigemasa TAKAI
  Osaka University

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