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Distributed Online Optimization for Multi-Agent Networks with Coupled Inequality Constraints

Research paper by Xiuxian Li, Xinlei Yi, Lihua Xie

Indexed on: 15 May '18Published on: 15 May '18Published in: arXiv - Mathematics - Optimization and Control



Abstract

This paper investigates the distributed online optimization problem over a multi-agent network subject to local set constraints and coupled inequality constraints, which has a large number of applications in practice, such as wireless sensor networks, power systems and plug-in electric vehicles. The same problem has been recently studied in [22], where a primal-dual algorithm is proposed with a sublinear regret analysis based on the assumptions that the communication graph is balanced and an algorithm generated parameter is bounded. However, it is inappropriate to assume the boundedness of a parameter generated by the designed algorithm. To overcome these problems, a modified primal-dual algorithm is developed in this paper, which does not rest on any parameter's boundedness assumption. Meanwhile, unbalanced communication graphs are considered here. It is shown that in such cases the proposed algorithm still has the sublinear regret. Finally, the theoretical results are verified by a simulation example.