Distributed Subgradient Algorithm for Multi-Agent Optimization With Dynamic Stepsize

作     者：Xiaoxing Ren Dewei Li Yugeng Xi Haibin Shao Xiaoxing Ren;Dewei Li;Yugeng Xi;Haibin Shao

作者机构：Department of AutomationShanghai Jiao Tong UniversityShanghai 200240China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2021年第8卷第8期

页      面：1451-1464页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

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) 

主　　题：Distributed optimization dynamic stepsize gradient method multi-agent networks 

摘      要：In this paper,we consider distributed convex optimization problems on multi-agent *** 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 *** approach can be applied to both synchronous and asynchronous communication ***,we propose the distributed subgradient with uncoordinated dynamic stepsizes(DS-UD)algorithm for synchronous protocol and the AsynDGD algorithm for asynchronous *** analysis shows that the proposed algorithms guarantee that all agents reach a consensus on the solution to the multi-agent optimization ***,the proposed approach with dynamic stepsizes eliminates the requirement of diminishing stepsize in existing *** examples of distributed estimation in sensor networks are provided to illustrate the effectiveness of the proposed approach.