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Abstract and Applied Analysis
Volume 2013, Article ID 376403, 9 pages
Research Article

A Decomposition Method with Redistributed Subroutine for Constrained Nonconvex Optimization

1School of Sciences, Shenyang University, Shenyang 110044, China
2School of Mathematical, Liaoning Normal University, Dalian 116029, China
3School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China

Received 6 September 2012; Revised 8 December 2012; Accepted 13 December 2012

Academic Editor: Jean M. Combes

Copyright © 2013 Yuan Lu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A class of constrained nonsmooth nonconvex optimization problems, that is, piecewise objectives with smooth inequality constraints are discussed in this paper. Based on the -theory, a superlinear convergent -algorithm, which uses a nonconvex redistributed proximal bundle subroutine, is designed to solve these optimization problems. An illustrative example is given to show how this convergent method works on a Second-Order Cone programming problem.