Paper Info
Title
Network Optimization via Smooth Exact Penalty Functions Enabled by Distributed Gradient Computation
Abstract
This article proposes a distributed algorithm for a network of agents to solve an optimization problem with separable objective function and locally coupled constraints. Our strategy is based on reformulating the original constrained problem as the unconstrained optimization of a smooth (continuously differentiable) exact penalty function. Computing the gradient of this penalty function in a distr...
Year
DOI
Venue
2021
10.1109/TCNS.2021.3068361
IEEE Transactions on Control of Network Systems
Keywords
DocType
Volume
Optimization,Mathematical model,Distributed algorithms,Linear programming,Linear matrix inequalities,Graph theory,Eigenvalues and eigenfunctions
Journal
8
Issue
ISSN
Citations 
3
2325-5870
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Priyank Srivastava102.03
Jorge Cortes21046113.95