Multi-agent constrained optimization of a strongly convex function over time-varying directed networks

Erfan Yazdandoost Hamedani, Necdet Serhat Aybat

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

1 Scopus citations

Abstract

We consider cooperative multi-agent consensus optimization problems over undirected and directed time-varying communication networks, where only local communications are allowed. The objective is to minimize the sum of agent-specific possibly non-smooth composite convex functions over agent-specific private conic constraint sets; hence, the optimal consensus decision should lie in the intersection of these private sets. Assuming the sum function is strongly convex, we provide convergence rates in sub-optimality, infeasibility and consensus violation; examine the effect of underlying network topology on the convergence rates of the proposed decentralized algorithm.

Original languageEnglish (US)
Title of host publication55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages518-525
Number of pages8
ISBN (Electronic)9781538632666
DOIs
StatePublished - Jan 17 2018
Event55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017 - Monticello, United States
Duration: Oct 3 2017Oct 6 2017

Publication series

Name55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
Volume2018-January

Other

Other55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017
CountryUnited States
CityMonticello
Period10/3/1710/6/17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Energy Engineering and Power Technology
  • Control and Optimization

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