Distributed multiuser optimization: Algorithms and error analysis

Jayash Koshal, Angelia Nedić, Uday V. Shanbhag

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

We consider a class of multiuser optimization problems in which user interactions are seen through congestion cost functions or coupling constraints. Our primary emphasis lies on the convergence and error analysis of distributed algorithms in which users communicate through aggregate user information. Traditional implementations are reliant on strong convexity assumptions, require coordination across users in terms of consistent stepsizes, and often rule out early termination by a group of users. We consider how some of these assumptions can be weakened in the context of projection methods motivated by fixed-point formulations of the problem. Specifically, we focus on (approximate) primal and primal-dual projection algorithms. We analyze the convergence behavior of the methods and provide error bounds in settings with limited coordination across users and regimes where a group of users may prematurely terminate affecting the convergence point.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4372-4377
Number of pages6
ISBN (Print)9781424438716
DOIs
StatePublished - 2009
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: Dec 15 2009Dec 18 2009

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Country/TerritoryChina
CityShanghai
Period12/15/0912/18/09

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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