Distributed Nonsmooth Convex Optimization over Markovian Switching Random Networks with Two Step-Sizes  

作　　者：YI Peng LI Li 

机构地区：[1]Department of Control Science and Engineering,Tongji University,and Shanghai Institute of Intelligent Science and Technology,Tongji University,Shanghai 200092,China

出　　处：《Journal of Systems Science & Complexity》2021年第4期1324-1344,共21页系统科学与复杂性学报（英文版）

基　　金：sponsored by Shanghai Sailing Program under Grant Nos.20YF1453000 and 20YF1452800;the National Natural Science Foundation of China under Grant No.62003239;the Fundamental Research Funds for the Central Universities under Grant Nos.22120200047 and 22120200048。

摘　　要：This paper investigates the distributed convex optimization problem over a multi-agent system with Markovian switching communication networks.The objective function is the sum of each agent’s local nonsmooth objective function,which cannot be known by other agents.The communication network is assumed to switch over a set of weight-balanced directed graphs with a Markovian property.The authors propose a consensus sub-gradient algorithm with two time-scale step-sizes to handle the Markovian switching topologies and the absence of global gradient information.With proper selection of step-sizes,the authors prove the almost sure convergence of all agents’local estimates to the same optimal solution when the union graph of the Markovian network’states is strongly connected and the Markovian chain is irreducible.The convergence rate analysis is also given for specific cases.Simulations are given to demonstrate the results.

关 键 词：Distributed optimization random graphs two time-scale algorithm 

分 类 号：O224[理学—运筹学与控制论]