Name
Title | ||
|---|---|---|
Distributed Algorithms For Solving Locally Coupled Optimization Problems On Agent Networks |
Abstract | ||
|---|---|---|
In this paper, we study the optimization problems for a group of agents whose individual objective functions and constraints may depend on the variables of neighboring agents. Several algorithms are proposed based on operator splitting techniques that can iteratively converge to an optimal primal (or dual) solution of the optimization problems. Then, via random coordinate updates, asynchronous implementations of the algorithms are developed with low computation and communication complexity and guaranteed almost sure convergence to an optimal solution. Numerical results are presented to illustrate the proposed algorithms. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CDC.2018.8619467 | 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC) |
Field | DocType | ISSN |
Convergence of random variables,Operator splitting,Asynchronous communication,Mathematical optimization,Computer science,Implementation,Communication complexity,Distributed algorithm,Optimization problem,Computation | Conference | 0743-1546 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianghai Hu | 1 | 520 | 64.76 |
| Yingying Xiao | 2 | 1 | 1.37 |
| Ji Liu | 3 | 146 | 26.61 |