A Scaled Central Path for Linear Optimization

Abstract:

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The central path is the most important in the design of interior-point algorithm for linear optimization. By an equivalence reformulation for the classical Newton direction, we give a new scaled central path, from which a new search direction is obtained. We derive the complexity bound for the full-step interior point algorithm based on this searching direction and the resulting complexity bound is the best-known for linear optimization.

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

683-686

DOI:

10.4028/www.scientific.net/AMR.204-210.683

Citation:

L. P. Zhang and Y. H. Xu, "A Scaled Central Path for Linear Optimization", Advanced Materials Research, Vols. 204-210, pp. 683-686, 2011

Online since:

February 2011

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Price:

$35.00

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