Extrapolated Smoothing Descent Algorithm for Constrained Nonconvex and Nonsmooth Composite Problems

被引:0
|
作者
Yunmei CHEN [1 ]
Hongcheng LIU [2 ]
Weina WANG [3 ]
机构
[1] Department of Mathematics, University of Florida
[2] Industrial and Systems Engineering, University of Florida
[3] Department of Mathematics, Hangzhou Dianzi
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中图分类号
O224 [最优化的数学理论];
学科分类号
摘要
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(afne-scaled) Clarke stationary point of the original nonsmooth and nonconvex problem. Their experimental results indicate the effectiveness of the proposed algorithm.
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页码:1049 / 1070
页数:22
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