ShanghaiTech University Knowledge Management System
Fenchel Dual Gradient Methods for Distributed Convex Optimization over Time-varying Networks | |
2017 | |
Source Publication | 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
![]() |
ISSN | 2334-3303 |
Volume | PP |
Issue | 99 |
Pages | 4629 - 4636 |
Status | 已发表 |
DOI | 10.1109/TAC.2019.2901829 |
Abstract | To date, a large collection of distributed algorithms for convex multi-agent optimization have been reported, yet only few of them converge to an optimal solution at guaranteed rates when the topologies of the agent networks are time-varying. Motivated by this, we develop a family of distributed Fenchel dual gradient methods for solving strongly convex yet non-smooth multi-agent optimization problems with nonidentical local constraints over time-varying networks. The proposed algorithms are constructed based on the application of weighted gradient methods to the Fenchel dual of the multiagent optimization problem. They are able to drive all the agents to dual optimality at an O(1/k) rate and to primal optimality at an O(1/root k) rate under a standard network connectivity condition. The competent convergence performance of the Fenchel dual gradient methods is demonstrated via numerical examples. |
Keyword | Gradient methods Convergence Convex functions Standards Linear programming |
Publication Place | 345 E 47TH ST, NEW YORK, NY 10017 USA |
Conference Place | Melbourne, VIC |
Conference Date | 12-15 Dec. 2017 |
URL | 查看原文 |
Indexed By | SCI ; EI ; CPCI ; SCIE |
Language | 英语 |
Funding Project | Natural Science Foundation of Shanghai[16ZR1422500] |
WOS Research Area | Automation & Control Systems ; Engineering |
WOS Subject | Automation & Control Systems ; Engineering, Electrical & Electronic |
WOS ID | WOS:000424696902127 |
Publisher | IEEE |
EI Accession Number | 20181805132494 |
EI Keywords | Convergence of numerical methods ; Convex optimization ; Gradient methods ; Multi agent systems |
EI Classification Number | Electric Networks:703.1 ; Numerical Methods:921.6 |
WOS Keyword | MODEL-PREDICTIVE CONTROL ; RESOURCE-ALLOCATION ; 1ST-ORDER METHODS ; DIRECTED-GRAPHS ; ALGORITHM ; CONSENSUS ; DECOMPOSITION |
Original Document Type | Proceedings Paper |
Source Data | IEEE |
Citation statistics | |
Document Type | 会议论文 |
Identifier | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/16323 |
Collection | 信息科学与技术学院 信息科学与技术学院_PI研究组_陆疌组 信息科学与技术学院_博士生 |
Corresponding Author | Jie Lu |
Affiliation | School of Information Science and Technology, ShanghaiTech University, Shanghai, China |
First Author Affilication | School of Information Science and Technology |
Corresponding Author Affilication | School of Information Science and Technology |
First Signature Affilication | School of Information Science and Technology |
Recommended Citation GB/T 7714 | Xuyang Wu,Jie Lu. Fenchel Dual Gradient Methods for Distributed Convex Optimization over Time-varying Networks[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2017:4629 - 4636. |
Files in This Item: | Download All | |||||
File Name/Size | DocType | Version | Access | License |
Edit Comment
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.