A survey of distributed optimization

T Yang, X Yi, J Wu, Y Yuan, D Wu, Z Meng… - Annual Reviews in …, 2019 - Elsevier
In distributed optimization of multi-agent systems, agents cooperate to minimize a global
function which is a sum of local objective functions. Motivated by applications including …

Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming

C Ning, F You - Computers & Chemical Engineering, 2019 - Elsevier
This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …

Dual decomposition for multi-agent distributed optimization with coupling constraints

A Falsone, K Margellos, S Garatti, M Prandini - Automatica, 2017 - Elsevier
We study distributed optimization in a cooperative multi-agent setting, where agents have to
agree on the usage of shared resources and can communicate via a time-varying network to …

Tracking-ADMM for distributed constraint-coupled optimization

A Falsone, I Notarnicola, G Notarstefano, M Prandini - Automatica, 2020 - Elsevier
We consider constraint-coupled optimization problems in which agents of a network aim to
cooperatively minimize the sum of local objective functions subject to individual constraints …

Distributed generalized Nash equilibrium seeking in aggregative games on time-varying networks

G Belgioioso, A Nedić… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We design the first fully distributed algorithm for generalized Nash equilibrium seeking in
aggregative games on a time-varying communication network, under partial-decision …

Distributed optimization for smart cyber-physical networks

G Notarstefano, I Notarnicola… - Foundations and Trends …, 2019 - nowpublishers.com
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 …

An energy sharing mechanism achieving the same flexibility as centralized dispatch

Y Chen, W Wei, H Wang, Q Zhou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Deploying distributed renewable energy at the demand side is an important measure to
implement a sustainable society. However, the massive small solar and wind generation …

Distributed proximal algorithms for multiagent optimization with coupled inequality constraints

X Li, G Feng, L Xie - IEEE Transactions on Automatic Control, 2020 - ieeexplore.ieee.org
This article aims to address distributed optimization problems over directed and time-varying
networks, where the global objective function consists of a sum of locally accessible convex …

The scenario approach: A tool at the service of data-driven decision making

MC Campi, A Carè, S Garatti - Annual Reviews in Control, 2021 - Elsevier
In the eyes of many control scientists, the theory of the scenario approach is a tool for
determining the sample size in certain randomized control-design methods, where an …

Neural-network-based fully distributed adaptive consensus for a class of uncertain multiagent systems

D Yue, J Cao, Q Li, Q Liu - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
In this article, we revisit the problem of distributed neuroadaptive consensus for uncertain
multiagent systems (MASs) in the presence of unmodeled nonlinearities as well as unknown …