A new simultaneous subgradient projection algorithm for solving a multiple-sets split feasibility problem
Applications of Mathematics (2014)
- Volume: 59, Issue: 1, page 37-51
- ISSN: 0862-7940
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topDang, Yazheng, and Gao, Yan. "A new simultaneous subgradient projection algorithm for solving a multiple-sets split feasibility problem." Applications of Mathematics 59.1 (2014): 37-51. <http://eudml.org/doc/260812>.
@article{Dang2014,
abstract = {In this paper, we present a simultaneous subgradient algorithm for solving the multiple-sets split feasibility problem. The algorithm employs two extrapolated factors in each iteration, which not only improves feasibility by eliminating the need to compute the Lipschitz constant, but also enhances flexibility due to applying variable step size. The convergence of the algorithm is proved under suitable conditions. Numerical results illustrate that the new algorithm has better convergence than the existing one.},
author = {Dang, Yazheng, Gao, Yan},
journal = {Applications of Mathematics},
keywords = {multiple-sets split feasibility problem; subgradient; extrapolated technique; multiple-sets split feasibility problem; subgradient; extrapolated technique},
language = {eng},
number = {1},
pages = {37-51},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {A new simultaneous subgradient projection algorithm for solving a multiple-sets split feasibility problem},
url = {http://eudml.org/doc/260812},
volume = {59},
year = {2014},
}
TY - JOUR
AU - Dang, Yazheng
AU - Gao, Yan
TI - A new simultaneous subgradient projection algorithm for solving a multiple-sets split feasibility problem
JO - Applications of Mathematics
PY - 2014
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 59
IS - 1
SP - 37
EP - 51
AB - In this paper, we present a simultaneous subgradient algorithm for solving the multiple-sets split feasibility problem. The algorithm employs two extrapolated factors in each iteration, which not only improves feasibility by eliminating the need to compute the Lipschitz constant, but also enhances flexibility due to applying variable step size. The convergence of the algorithm is proved under suitable conditions. Numerical results illustrate that the new algorithm has better convergence than the existing one.
LA - eng
KW - multiple-sets split feasibility problem; subgradient; extrapolated technique; multiple-sets split feasibility problem; subgradient; extrapolated technique
UR - http://eudml.org/doc/260812
ER -
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