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Volume 19, Issue 1
A Scaled Central Path for Linear Programming

Ya-Xiang Yuan

J. Comp. Math., 19 (2001), pp. 35-40.

Published online: 2001-02

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  • Abstract

Interior point methods are very efficient methods for solving large scale linear programming problems. The central path plays a very important role in interior point methods. In this paper we propose a new central path, which scales the variables. Thus it has the advantage of forcing the path to have roughly the same distance from each active constraint boundary near the solution.

  • Keywords

Central path, Interior point methods, Linear programming.

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COPYRIGHT: © Global Science Press

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@Article{JCM-19-35, author = {Yuan , Ya-Xiang}, title = {A Scaled Central Path for Linear Programming}, journal = {Journal of Computational Mathematics}, year = {2001}, volume = {19}, number = {1}, pages = {35--40}, abstract = {

Interior point methods are very efficient methods for solving large scale linear programming problems. The central path plays a very important role in interior point methods. In this paper we propose a new central path, which scales the variables. Thus it has the advantage of forcing the path to have roughly the same distance from each active constraint boundary near the solution.

}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/8955.html} }
TY - JOUR T1 - A Scaled Central Path for Linear Programming AU - Yuan , Ya-Xiang JO - Journal of Computational Mathematics VL - 1 SP - 35 EP - 40 PY - 2001 DA - 2001/02 SN - 19 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/8955.html KW - Central path, Interior point methods, Linear programming. AB -

Interior point methods are very efficient methods for solving large scale linear programming problems. The central path plays a very important role in interior point methods. In this paper we propose a new central path, which scales the variables. Thus it has the advantage of forcing the path to have roughly the same distance from each active constraint boundary near the solution.

Yuan , Ya-Xiang. (2001). A Scaled Central Path for Linear Programming. Journal of Computational Mathematics. 19 (1). 35-40. doi:
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