Paper Title:
Parallel Iterative Methods for Nonlinear Programming Problems
  Abstract

In this paper, we present two parallel multiplicative algorithms for convex programming. If the objective function is differentiable and convex on the positive orthant of , and it has compact level sets and has a locally Lipschitz continuous gradient, we prove these algorithms converge to a solution of minimization problem. For the proofs there are essentially used the results of sequential methods shown by Eggermont[1].

  Info
Periodical
Edited by
Dehuai Zeng
Pages
105-110
DOI
10.4028/www.scientific.net/AMR.159.105
Citation
Z. Chen, "Parallel Iterative Methods for Nonlinear Programming Problems", Advanced Materials Research, Vol. 159, pp. 105-110, 2011
Online since
December 2010
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