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Two parallel distribution algorithms for convex constrained minimization problems
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DOI：10.1016/j.amc.2006.08.167.png)
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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.
Keyword:
nonsmooth optimization
parallel algorithm
convex programming
Moreau-Yosida regularization
期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
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