Title
An Inexact Dual Fast Gradient-Projection Method for Separable Convex Optimization with Linear Coupled Constraints.
Abstract
In this paper, a class of separable convex optimization problems with linear coupled constraints is studied. According to the Lagrangian duality, the linear coupled constraints are appended to the objective function. Then, a fast gradient-projection method is introduced to update the Lagrangian multiplier, and an inexact solution method is proposed to solve the inner problems. The advantage of our proposed method is that the inner problems can be solved in an inexact and parallel manner. The established convergence results show that our proposed algorithm still achieves optimal convergence rate even though the inner problems are solved inexactly. Finally, several numerical experiments are presented to illustrate the efficiency and effectiveness of our proposed algorithm.
Year
DOI
Venue
2016
10.1007/s10957-015-0757-1
Journal of Optimization Theory and Applications
Keywords
Field
DocType
Convex optimization, Dual decomposition, Inexact gradient method, Suboptimality and constraint violations, 90C25, 90C46, 65Y05
Convergence (routing),Mathematical optimization,Lagrange multiplier,Separable space,Gradient projection,Rate of convergence,Lagrangian duality,Convex optimization,Mathematics
Journal
Volume
Issue
ISSN
168
1
1573-2878
Citations 
PageRank 
References 
8
0.47
21
Authors
5
Name
Order
Citations
PageRank
Jueyou Li1261.49
Zhiyou Wu2355.35
Changzhi Wu319519.07
Qiang Long4362.40
xiangyu wang515822.91