# Distributed Subgradient-Based Multiagent Optimization With More General Step Sizes

@article{Wang2018DistributedSM, title={Distributed Subgradient-Based Multiagent Optimization With More General Step Sizes}, author={Peng Wang and Peng Lin and Wei Ren and Yongduan Song}, journal={IEEE Transactions on Automatic Control}, year={2018}, volume={63}, pages={2295-2302} }

A wider selection of step sizes is explored for the distributed subgradient algorithm for multigent optimization problems with time-varying and balanced communication topologies. The square summable requirement of the step sizes commonly adopted in the literature is removed. The step sizes are only required to be positive, vanishing, and nonsummable, which provides the possibility for better convergence rates. Both unconstrained and constrained optimization problems are considered. It is proved…

## 22 Citations

Distributed Subgradient Algorithm for Multi-agent Optimization with Uncoordinated Dynamic Stepsizes

- Computer Science2020 IEEE 16th International Conference on Control & Automation (ICCA)
- 2020

Theoretical analysis shows that the proposed algorithm leads all agents to reach a consensus on the optimal solution to the optimization problem, and the dynamic stepsizes can overcome inefficient calculations caused by the diminishing stepsizes in the existing distributed subgradient methods.

Distributed Event-Triggered Subgradient Method for Convex Optimization With General Step-Size

- Computer ScienceIEEE Access
- 2020

A distributed projective subgradient algorithm is designed for time-varying directed communication topologies under the event-triggered mechanism and the consensus and optimization of the system state and the ergodic average sequence are discussed.

Distributed Subgradient Algorithm for Multi-Agent Optimization With Dynamic Stepsize

- Computer ScienceIEEE/CAA Journal of Automatica Sinica
- 2021

Theoretical analysis shows that the proposed algorithms guarantee that all agents reach a consensus on the solution to the multi-agent optimization problem, and the proposed approach with dynamic stepsizes eliminates the requirement of diminishing stepsize in existing works.

Distributed Optimization Algorithm for Discrete-Time Heterogeneous Multi-Agent Systems With Nonuniform Stepsizes

- Computer ScienceIEEE Access
- 2019

By the properties of the stochastic matrix, it is proven that all agents’ position states can converge to the optimal solution of a team objective function provided the union communication topology is strongly connected.

Distributed constrained optimization for multi-agent networks with nonsmooth objective functions

- Computer ScienceSyst. Control. Lett.
- 2019

A novel distributed continuous-time algorithm is proposed to solve distributed constrained optimization problem in multi-agent systems, where agents cooperatively minimize an objective function being the sum of each agent’s objective function while meeting equality and inequality constraints.

Distributed Proximal Algorithms for Multiagent Optimization With Coupled Inequality Constraints

- Computer Science, MathematicsIEEE Transactions on Automatic Control
- 2021

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 objective…

Distributed Optimization with Coupling Constraints via Dual Proximal Gradient Method and Applications to Asynchronous Networks

- 2021

In this paper, we consider solving a distributed optimization problem (DOP) with coupling constraints in a multiagent network based on proximal gradient method. In this problem, each agent aims to…

Randomized Block Proximal Methods for Distributed Stochastic Big-Data Optimization

- Computer Science, MathematicsIEEE Transactions on Automatic Control
- 2021

A class of novel distributed algorithms for solving stochastic big-data convex optimization problems over directed graphs, where the dimension of the decision variable can be extremely high and the objective function can be nonsmooth, is introduced.

Distributed quadratic optimisation for linear multi‐agent systems over jointly connected networks

- Computer ScienceIET Control Theory & Applications
- 2019

The authors propose a distributed observer for each agent such that other agents' cost functions are obtained and the state feedback and output feedback optimal algorithms are designed based on the output of the distributed observer.

A survey of distributed optimization

- Computer ScienceAnnu. Rev. Control.
- 2019

This survey paper aims to offer a detailed overview of existing distributed optimization algorithms and their applications in power systems, and focuses on the application of distributed optimization in the optimal coordination of distributed energy resources.

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