On distributed optimization under inequality and equality constraints via penalty primal-dual methods

Minghui Zhu, Sonia Martínez

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

9 Scopus citations

Abstract

We consider a multi-agent convex optimization problem where the agents are to minimize a sum of local objective functions subject to a global inequality constraint, a global equality constraint and a global constraint set. We devise a distributed primal-dual subgradient algorithm which is based on the characterization of the primal-dual optimal solutions as the saddle points of the penalty function. This algorithm allows the agents exchange information over networks with time-varying topologies and asymptotically agree on an optimal solution and the optimal value.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
Pages2434-2439
Number of pages6
StatePublished - 2010
Event2010 American Control Conference, ACC 2010 - Baltimore, MD, United States
Duration: Jun 30 2010Jul 2 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

Other

Other2010 American Control Conference, ACC 2010
CountryUnited States
CityBaltimore, MD
Period6/30/107/2/10

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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    Zhu, M., & Martínez, S. (2010). On distributed optimization under inequality and equality constraints via penalty primal-dual methods. In Proceedings of the 2010 American Control Conference, ACC 2010 (pp. 2434-2439). [5530577] (Proceedings of the 2010 American Control Conference, ACC 2010).