Title
A Distributed Continuous-Time Algorithm for Nonsmooth Constrained Optimization
Abstract
This article studies a distributed convex optimization problem with nonsmooth local objective functions subject to local inequality constraints and a coupled equality constraint. By combining the dual decomposition technique and subgradient flow method, a new distributed solution is developed in continuous time. Unlike the existing related continuous-time schemes either depending on specific initial conditions or on differentiability or strict (even strong) convexity of local cost functions, this study is free of initialization and takes into account general convex local objective functions which could be nonsmooth. Via nonsmooth analysis and set-valued LaSalle invariance principle, it is proved that a global optimal solution can be asymptotically obtained. Finally, the effectiveness of our algorithm is illustrated by numerical examples.
Year
DOI
Venue
2020
10.1109/TAC.2020.2965905
IEEE Transactions on Automatic Control
Keywords
DocType
Volume
Constrained optimization,distributed convex optimization,multiagent systems,nonsmooth analysis
Journal
65
Issue
ISSN
Citations 
11
0018-9286
1
PageRank 
References 
Authors
0.35
10
4
Name
Order
Citations
PageRank
Gang Chen1174.63
Qing Yang2111.53
Yong-Duan Song31949108.61
FRANK L. LEWIS45782402.68