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Distributed Constrained Convex Optimization with Accumulated Subgradient Information over Undirected Switching Networks Yuichi KAJIYAMA Naoki HAYASHI Shigemasa TAKAI Publication IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E102-A No.2 pp.343-350 Publication Date: 2019/02/01 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: Keyword: convex optimization, multi-agent systems, distributed subgradient method, Full Text: PDF(1.5MB)>>
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. | ||||||||||
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