Averaging approach to distributed convex optimization for continuous-time multi-agent systems

Wei Ni; Xiaoli Wang

Kybernetika (2016)

  • Volume: 52, Issue: 6, page 898-913
  • ISSN: 0023-5954

Abstract

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Recently, distributed convex optimization has received much attention by many researchers. Current research on this problem mainly focuses on fixed network topologies, without enough attention to switching ones. This paper specially establishes a new technique called averaging-base approach to design a continuous-time distributed algorithm for convex optimization problem under switching topology. This idea of using averaging was proposed in our earlier works for the consensus problem of multi-agent systems under switching topology, and it is further developed in this paper to gain further insight into the distributed optimization algorithm. Key techniques are used, such as two-time-scale analysis and asymptotic expansions for the solutions of the backward equation or Liouvill equation. Important results are obtained, including weak convergence of our algorithm to the optimal solution.

How to cite

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Ni, Wei, and Wang, Xiaoli. "Averaging approach to distributed convex optimization for continuous-time multi-agent systems." Kybernetika 52.6 (2016): 898-913. <http://eudml.org/doc/287870>.

@article{Ni2016,
abstract = {Recently, distributed convex optimization has received much attention by many researchers. Current research on this problem mainly focuses on fixed network topologies, without enough attention to switching ones. This paper specially establishes a new technique called averaging-base approach to design a continuous-time distributed algorithm for convex optimization problem under switching topology. This idea of using averaging was proposed in our earlier works for the consensus problem of multi-agent systems under switching topology, and it is further developed in this paper to gain further insight into the distributed optimization algorithm. Key techniques are used, such as two-time-scale analysis and asymptotic expansions for the solutions of the backward equation or Liouvill equation. Important results are obtained, including weak convergence of our algorithm to the optimal solution.},
author = {Ni, Wei, Wang, Xiaoli},
journal = {Kybernetika},
keywords = {distributed convex optimization; averaging approach; two-time-scale; Markovian switching; invariant measure},
language = {eng},
number = {6},
pages = {898-913},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Averaging approach to distributed convex optimization for continuous-time multi-agent systems},
url = {http://eudml.org/doc/287870},
volume = {52},
year = {2016},
}

TY - JOUR
AU - Ni, Wei
AU - Wang, Xiaoli
TI - Averaging approach to distributed convex optimization for continuous-time multi-agent systems
JO - Kybernetika
PY - 2016
PB - Institute of Information Theory and Automation AS CR
VL - 52
IS - 6
SP - 898
EP - 913
AB - Recently, distributed convex optimization has received much attention by many researchers. Current research on this problem mainly focuses on fixed network topologies, without enough attention to switching ones. This paper specially establishes a new technique called averaging-base approach to design a continuous-time distributed algorithm for convex optimization problem under switching topology. This idea of using averaging was proposed in our earlier works for the consensus problem of multi-agent systems under switching topology, and it is further developed in this paper to gain further insight into the distributed optimization algorithm. Key techniques are used, such as two-time-scale analysis and asymptotic expansions for the solutions of the backward equation or Liouvill equation. Important results are obtained, including weak convergence of our algorithm to the optimal solution.
LA - eng
KW - distributed convex optimization; averaging approach; two-time-scale; Markovian switching; invariant measure
UR - http://eudml.org/doc/287870
ER -

References

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