Parallel Iterative Methods for Nonlinear Programming Problems

Abstract:

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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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Price:

$35.00

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