• DocumentCode
    115407
  • Title

    A primal-dual algorithm for distributed optimization

  • Author

    Bianchi, P. ; Hachem, W.

  • Author_Institution
    LTCI, Telecom ParisTech., Paris, France
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    4240
  • Lastpage
    4245
  • Abstract
    Consider a set of N agents who cooperate to solve the problem infx Σn=1N (fn (x) + gn (x)) where the convex cost functions (fn, gn) are local to the agent n. It is assumed that the functions fn are differentiable and have Lipschitz gradients. In this paper, a primal-dual algorithm for distributively solving this problem is proposed. This algorithm is an instance of a primal-dual algorithm separately introduced by Ṽu and Condat.
  • Keywords
    multi-agent systems; optimisation; set theory; Lipschitz gradients; convex cost functions; differentiable gradients; distributed optimization; primal-dual algorithm; Clustering algorithms; Convergence; Cost function; Equations; Minimization; Next generation networking; Radio frequency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7040050
  • Filename
    7040050
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=115407