IRI - Accelerated multi-agent optimization method over stochastic networks

Publication

Accelerated multi-agent optimization method over stochastic networks

Conference Article

Conference

IEEE Conference on Decision and Control (CDC)

Edition

59th

Pages

2961-2966

Doc link

http://dx.doi.org/10.1109/CDC42340.2020.9304307

File

Download the digital copy of the doc pdf document

Authors

Abstract

We propose a distributed method to solve a multi-agent optimization problem with strongly convex cost function and equality coupling constraints. The method is based on Nesterov’s accelerated gradient approach and works over stochastically time-varying communication networks. We consider the standard assumptions of Nesterov’s method and show that the sequence of the expected dual values converge toward the optimal value with the rate of O(1/k²). Furthermore, we provide a simulation study of solving an optimal power flow problem with a well-known benchmark case.

Author keywords

multi-agent optimization, distributed method, accelerated gradient method, distributed optimal power flow problem

Scientific reference

W. Ananduta, C. Ocampo-Martínez and A. Nedic. Accelerated multi-agent optimization method over stochastic networks, 59th IEEE Conference on Decision and Control, 2020, Jeju Island, Republic of Korea, pp. 2961-2966, IEEE.