A Scaled Central Path for Linear Optimization

Li Pu Zhang; Ying Hong Xu

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 204-210A Scaled Central Path for Linear Optimization

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.

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Periodical:

Advanced Materials Research (Volumes 204-210)

Pages:

683-686

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.204-210.683

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Online since:

February 2011

Authors:

Li Pu Zhang, Ying Hong Xu

Keywords:

Central Path, Complexity Bound, Full-Newton Step, Interior-Point Algorithm, Linear Optimization

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References

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