Distributed stochastic mirror descent algorithm for resource allocation problem

	Distributed stochastic mirror descent algorithm for resource allocation problem
	Wang Yinghui; Tu Zhipeng; Qin Huashu
刊名	Control Theory and Technology
	2020
卷号	18 期号:4 页码:339-347
关键词	Distributed Resource allocation problem Stochastic gradient Mirror descent
ISSN号	2095-6983
英文摘要	In this paper, we consider a distributed resource allocation problem of minimizing a global convex function formed by a sum of local convex functions with coupling constraints. Based on neighbor communication and stochastic gradient, a distributed stochastic mirror descent algorithm is designed for the distributed resource allocation problem. Sublinear convergence to an optimal solution of the proposed algorithm is given when the second moments of the gradient noises are summable. A numerical example is also given to illustrate the effectiveness of the proposed algorithm.
语种	英语
CSCD记录号	CSCD:6870881
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/58369]
专题	中国科学院数学与系统科学研究院
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Wang Yinghui,Tu Zhipeng,Qin Huashu. Distributed stochastic mirror descent algorithm for resource allocation problem[J]. Control Theory and Technology,2020,18(4):339-347.
APA	Wang Yinghui,Tu Zhipeng,&Qin Huashu.(2020).Distributed stochastic mirror descent algorithm for resource allocation problem.Control Theory and Technology,18(4),339-347.
MLA	Wang Yinghui,et al."Distributed stochastic mirror descent algorithm for resource allocation problem".Control Theory and Technology 18.4(2020):339-347.