Distributed Subgradient Algorithm for Multi-Agent Optimization With Dynamic Stepsize  

作　　者：Xiaoxing Ren Dewei Li Yugeng Xi Haibin Shao 

机构地区：[1]Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2021年第8期1451-1464,共14页自动化学报（英文版）

基　　金：supported by the Key Research and Development Project in Guangdong Province(2020B0101050001);the National Science Foundation of China(61973214,61590924,61963030);the Natural Science Foundation of Shanghai(19ZR1476200)。

摘　　要：In this paper,we consider distributed convex optimization problems on multi-agent networks.We develop and analyze the distributed gradient method which allows each agent to compute its dynamic stepsize by utilizing the time-varying estimate of the local function value at the global optimal solution.Our approach can be applied to both synchronous and asynchronous communication protocols.Specifically,we propose the distributed subgradient with uncoordinated dynamic stepsizes(DS-UD)algorithm for synchronous protocol and the AsynDGD algorithm for asynchronous protocol.Theoretical analysis shows that the proposed algorithms guarantee that all agents reach a consensus on the solution to the multi-agent optimization problem.Moreover,the proposed approach with dynamic stepsizes eliminates the requirement of diminishing stepsize in existing works.Numerical examples of distributed estimation in sensor networks are provided to illustrate the effectiveness of the proposed approach.

关 键 词：Distributed optimization dynamic stepsize gradient method multi-agent networks 

分 类 号：O224[理学—运筹学与控制论]