Parallel Iterative Methods for Nonlinear Programming Problems

Zhong Chen

doi:10.4028/www.scientific.net/AMR.159.105

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 159Parallel Iterative Methods for Nonlinear...

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].

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Periodical:

Advanced Materials Research (Volume 159)

Pages:

105-110

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.159.105

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Online since:

December 2010

Authors:

Zhong Chen

Keywords:

Convergence, Iterative Method, Nonlinear Programming, Parallel Computation

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References

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