Decentralized optimization algorithm of networked systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider a large-scale networked system which consists of multiple subsystems. With decentralized optimization algorithms, each subsystem can cooperate with other ones to obtain the optimal solution to an optimization problem. This paper presents a decentralized optimization algorithm based on penalty functions. Rather than most existing decentralized optimization algorithms, this algorithm does not require convexity of optimization problem. Firstly, the coupling between subsystems is reduced by variable splitting method. Then, the penalty function is introduced to weaken the restriction on subsystems. With knowledge of its neighboring subsystems, each subsystem can obtain the local/global optimal solution of the original optimization problem. Illustrative examples are presented for demonstration.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Pages2849-2854
Number of pages6
ISBN (Electronic)9789881563910
DOIs
StatePublished - 26 Aug 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 201629 Jul 2016

Publication series

NameChinese Control Conference, CCC
Volume2016-August
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference35th Chinese Control Conference, CCC 2016
Country/TerritoryChina
CityChengdu
Period27/07/1629/07/16

Keywords

  • Decentralized
  • Networked system
  • Optimization

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