重庆工商大学学报（自然科学版）2017，Vol.34Issue(1)：34-40,7.DOI:10.16055/j.issn.1672-058X.2017.0000.007
一种解可分凸优化问题的外梯度并行分裂算法
An Extragradient Parallel Split Algorith m for Solving Separable Convex Opti mization Proble m
摘要
Abstract
Parallel splitting method is an important method for solving the convex optimization problem with two separable variables.The methods usually requires that the two convex functions have relatively easy proximal mappings,for the structure that only one of the two functions has easy proximal mapping and the other one is smoothly convex but does not have an easy proximal mapping.We propose in this paper an extragradient algorithm based on parallel splitting.Under the assumption that the smooth function has a Lipschitz continuous gradient condition,we prove the O(1/ε)iteration complexity of the method.关键词
凸优化/可分离结构/增广拉格朗日法/并行分裂法Key words
convex optimization/separable structure/augmented Lagrangian method/parallel splitting method分类
数理科学引用本文复制引用
程鹏..一种解可分凸优化问题的外梯度并行分裂算法[J].重庆工商大学学报（自然科学版）,2017,34(1):34-40,7.基金项目
重庆市自然科学基金（CSTC2015JCYJBX0029）． （）
