Nowadays, a large amount of information has to be transmitted or processed. This implies
high-power processing, large memory density, and increased energy consumption. In …

This paper reviews distributed/decentralized algorithms to solve the optimal power flow
(OPF) problem in electric power systems. Six decomposition coordination algorithms are …

Multi-agent systems (MASs) are typically composed of multiple smart entities with
independent sensing, communication, computing, and decision-making capabilities …

Consider the consensus problem of minimizing f(x)=i=1^nf_i(x), where x∈R^p and each f_i
is only known to the individual agent i in a connected network of n agents. To solve this …

Distributed optimal power flow (OPF) is a challenging non-linear, non-convex problem of
central importance to the future power grid. Although many approaches are currently …

In this letter, we study distributed optimization, where a network of agents, abstracted as a
directed graph, collaborates to minimize the average of locally known convex functions …

Multi-agent distributed consensus optimization problems arise in many signal processing
applications. Recently, the alternating direction method of multipliers (ADMM) has been …

We study distributed optimization problems when N nodes minimize the sum of their
individual costs subject to a common vector variable. The costs are convex, have Lipschitz …

Various distributed optimization methods have been developed for solving problems which
have simple local constraint sets and whose objective function is the sum of local cost …

Decentralized optimization to minimize a finite sum of functions, distributed over a network of
nodes, has been a significant area within control and signal-processing research due to its …