Global Convergence of a New Conjugate Gradient Method with Wolfe Type Line Search
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@Article{JICS-7-067,
author = {Y.y. Chen},
title = {Global Convergence of a New Conjugate Gradient Method with Wolfe Type Line Search},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {7},
number = {1},
pages = {067--071},
abstract = { In this paper, a new nonlinear conjugate gradient methods with wolfe type line search for
solving unstrained optimization problems is proposed. The direction generated by the new methods produce
sufficient descent search direction. Under some conditions, we give the global convergence results for the
new nonlinear conjugate gradient methods with Wolfe type line search. Finally, the numerical results show
that the new method is also efficient for general unconstrained optimizations.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22663.html}
}
TY - JOUR
T1 - Global Convergence of a New Conjugate Gradient Method with Wolfe Type Line Search
AU - Y.y. Chen
JO - Journal of Information and Computing Science
VL - 1
SP - 067
EP - 071
PY - 2024
DA - 2024/01
SN - 7
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22663.html
KW -
AB - In this paper, a new nonlinear conjugate gradient methods with wolfe type line search for
solving unstrained optimization problems is proposed. The direction generated by the new methods produce
sufficient descent search direction. Under some conditions, we give the global convergence results for the
new nonlinear conjugate gradient methods with Wolfe type line search. Finally, the numerical results show
that the new method is also efficient for general unconstrained optimizations.
Y.y. Chen. (2024). Global Convergence of a New Conjugate Gradient Method with Wolfe Type Line Search.
Journal of Information and Computing Science. 7 (1).
067-071.
doi:
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