Two parallel distribution algorithms for convex constrained minimization problems

doi:10.1016/j.amc.2006.08.167

Two parallel distribution algorithms for convex constrained minimization problems

2007-03-01

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DOI：10.1016/j.amc.2006.08.167

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A parallel gradient distribution (PGD) approach for minimizing a nonsmooth convex function on a block-separable convex set X of R '' and a parallel variable distribution (PVD) approach for minimizing a nonsmooth convex function on an inseparable closed convex set X of R-n are presented, which are constructed by using the Moreau-Yosida regularization of the convex functions. The convergence analysis for the two approaches is given as well. (c) 2006 Elsevier Inc. All rights reserved.

Keywords:

nonsmooth optimization

parallel algorithm

convex programming

Moreau-Yosida regularization

Two parallel distribution algorithms for convex constrained minimization problems

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