The presence of embedded electronics and communication capabilities as well as sensing
and control in smart devices has given rise to the novel concept of cyber-physical networks …

Several interesting problems in multi-robot systems can be cast in the framework of
distributed optimization. Examples include multi-robot task allocation, vehicle routing, target …

When it comes to solving the optimization problem of wind power and large-scale electric
vehicle (EV) synergistic access to the power grid, issues like the difficulty of accurately …

This article develops a proximal primal-dual decentralized strategy for multiagent
optimization problems that involve multiple coupled affine constraints, where each constraint …

Multi-agent decision problems are typically solved via distributed iterative algorithms, where
the agents only communicate between themselves on a peerto-peer network. Each agent …

In this work, we study the problem of unconstrained convex optimization in a fully distributed
multiagent setting, which includes asynchronous computation and lossy communication. In …

This paper considers an unconstrained collaborative optimization of a sum of convex
functions, where agents make decisions using local information in the presence of random …

Sparse optimization involving the L 0-norm function as the regularization in objective
function has a wide application in many fields. In this paper, we propose a projected neural …

We address the problem of multi-agent partition-based convex optimization which arises, for
example, in robot localization problems and in regional state estimation in smart grids. More …

Dual decomposition is widely utilized in the distributed optimization of multiagent systems. In
practice, the dual decomposition algorithm is desired to admit an asynchronous …