Distributed Proximal Algorithms for Multiagent Optimization with Coupled Inequality Constraints
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Article number | 9075384 |
Pages (from-to) | 1223-1230 |
Journal / Publication | IEEE Transactions on Automatic Control |
Volume | 66 |
Issue number | 3 |
Online published | 21 Apr 2020 |
Publication status | Published - Mar 2021 |
Link(s)
Abstract
This article aims to address distributed optimization problems over directed and time-varying networks, where the global objective function consists of a sum of locally accessible convex objective functions subject to a feasible set constraint and coupled inequality constraints whose information is only partially accessible to each agent. For this problem, a distributed proximal-based algorithm, called distributed proximal primal-dual algorithm, is proposed based on the celebrated centralized proximal point algorithm. It is shown that the proposed algorithm can lead to the global optimal solution with a general step size, which is diminishing and nonsummable, but not necessarily square summable, and the saddle-point running evaluation error vanishes proportionally to O(1/√k), where k > 0 is the iteration number. Finally, a simulation example is presented to corroborate the effectiveness of the proposed algorithm.
Research Area(s)
- Coupled inequality constraints, distributed optimization, multiagent networks, proximal point algorithm (PPA)
Citation Format(s)
Distributed Proximal Algorithms for Multiagent Optimization with Coupled Inequality Constraints. / Li, Xiuxian; Feng, Gang; Xie, Lihua.
In: IEEE Transactions on Automatic Control, Vol. 66, No. 3, 9075384, 03.2021, p. 1223-1230.
In: IEEE Transactions on Automatic Control, Vol. 66, No. 3, 9075384, 03.2021, p. 1223-1230.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review