首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Extrapolated Smoothing Descent Algorithm for Constrained Nonconvex and Nonsmooth Composite Problems*
Authors:Yunmei CHEN  Hongcheng LIU  Weina WANG
Institution:Department of Mathematics, University of Florida, Gainesville 118105, USA.;Industrial and Systems Engineering, University of Florida, Gainesville 118105, USA.; Corresponding author. Department of Mathematics, Hangzhou Dianzi University, Hangzhou 310018,China.
Abstract:In this paper, the authors propose a novel smoothing descent type algorithm with extrapolation for solving a class of constrained nonsmooth and nonconvex problems,where the nonconvex term is possibly nonsmooth. Their algorithm adopts the proximal gradient algorithm with extrapolation and a safe-guarding policy to minimize the smoothed objective function for better practical and theoretical performance. Moreover, the algorithm uses a easily checking rule to update the smoothing parameter to ensure that any accumulation point of the generated sequence is an (affine-scaled) Clarke stationary point of the original nonsmooth and nonconvex problem. Their experimental results indicate the effectiveness of the proposed algorithm.
Keywords:Constrained nonconvex and nonsmooth optimization  Smooth approximation  Proximal gradient algorithm with extrapolation  Gradient descent algorithm  Image reconstruction
点击此处可从《数学年刊B辑(英文版)》浏览原始摘要信息
点击此处可从《数学年刊B辑(英文版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号