An approximate redistributed proximal bundle method with inexact data for minimizing nonsmooth nonconvex functions
type: Item
instance of: scholarly article
title: An approximate redistributed proximal bundle method with inexact data for minimizing nonsmooth nonconvex functions
zbMATH Open document ID: 1394.90561
DOI: 10.1155/2015/215310
author: Jie Shen
author: Xiaoqian Liu
author: Fangfang Guo
author: Shuxin Wang
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: We describe an extension of the redistributed technique form classical proximal bundle method to the inexact situation for minimizing nonsmooth nonconvex functions. The cutting-planes model we construct is not the approximation to the whole nonconvex function, but to the local convexification of the approximate objective function, and this kind of local convexification is modified dynamically in order to always yield nonnegative linearization errors. Since we only employ the approximate function values and approximate subgradients, theoretical convergence analysis shows that an approximate stationary point or some double approximate stationary point can be obtained under some mild conditions.
Mathematics Subject Classification ID: 90C56
Mathematics Subject Classification ID: 90C26
zbMATH DE Number: 6925789
describes a project that uses: PNEW
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/215310
OpenAlex ID: W1503443042
Wikidata QID: Q59117637
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description: scientific article; zbMATH DE number 6925789