Paper Title:
A Scaled Central Path for Linear Optimization
  Abstract

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, 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
$32.00
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