Wireless network

Dual (grammatical number)

Mathematics

Regret

Wireless

Evolutionary biology

Biology

Distributed computing

Literature

Mathematical optimization

Distributed algorithm

Sublinear function

Machine learning

Mathematical analysis

Optimization problem

Function (biology)

Set (abstract data type)

Programming language

Computer science

Telecommunications

IEEE Transactions on Automatic Control

This article investigates the distributed online optimization problem over a multi-agent network subject to local set constraints and coupled inequality constraints, which has a lot of applications in many areas, such as wireless sensor networks, power systems, and plug-in electric vehicles. In this problem, the cost function at each time step is the sum of local cost functions with each of them being gradually revealed to its corresponding agent, and meanwhile only local functions in coupled inequality constraints are accessible to each agent. To address this problem, a modified primal-dual algorithm, called distributed online primal-dual push-sum algorithm, is developed in this article, which does not rest on any assumption on parameter boundedness and is applicable to unbalanced networks. It is shown that the proposed algorithm is sublinear for both the dynamic regret and the violation of coupled inequality constraints. Finally, the theoretical results are supported by a simulation example.

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