A smoothing Newton method for the minimum norm solution of linear program
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@Article{JICS-9-267,
author = {Lina Zhang and Zhensheng Yu and Yanyan Zhu},
title = {A smoothing Newton method for the minimum norm solution of linear program},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {9},
number = {4},
pages = {267--276},
abstract = {In this paper, we propose a smoothing Newton method to find the minimum norm solution of
linear program problems. By using the smoothing technique, we reformulate the problem as an unconstrained
minimization problem with a twice continuous differentiable objective function. The minimization of this
objective function can be carried out by the classical Newton-type method which is shown to be globally
convergence.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22570.html}
}
TY - JOUR
T1 - A smoothing Newton method for the minimum norm solution of linear program
AU - Lina Zhang and Zhensheng Yu and Yanyan Zhu
JO - Journal of Information and Computing Science
VL - 4
SP - 267
EP - 276
PY - 2024
DA - 2024/01
SN - 9
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22570.html
KW - Linear program, Minimum norm solution, Unconstrained minimization reformulation,
Smoothing function, Newton-type method.
AB - In this paper, we propose a smoothing Newton method to find the minimum norm solution of
linear program problems. By using the smoothing technique, we reformulate the problem as an unconstrained
minimization problem with a twice continuous differentiable objective function. The minimization of this
objective function can be carried out by the classical Newton-type method which is shown to be globally
convergence.
Lina Zhang and Zhensheng Yu and Yanyan Zhu. (2024). A smoothing Newton method for the minimum norm solution of linear program.
Journal of Information and Computing Science. 9 (4).
267-276.
doi:
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