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A superlinear space decomposition algorithm for constrained nonsmooth convex program

Release Time:2019-03-09  Hits:

Indexed by: Journal Article

Date of Publication: 2010-05-01

Journal: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

Included Journals: Scopus、EI、SCIE

Volume: 234

Issue: 1

Page Number: 224-232

ISSN: 0377-0427

Key Words: Nonsmooth optimization; Piecewise C(2); VU decomposition; Second-order expansion

Abstract: A class of constrained nonsmooth convex optimization problems, that is, piecewise C(2) convex objectives with smooth convex inequality constraints are transformed into unconstrained nonsmooth convex programs with the help of exact penalty function. The objective functions of these unconstrained programs are particular cases of functions with primal-dual gradient structure which has connection with Vu space decomposition. Then a VU space decomposition method for solving this unconstrained program is presented. This method is proved to converge with local superlinear rate under certain assumptions. An illustrative example is given to show how this method works. (C) 2009 Elsevier B.V. All rights reserved.

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