TY - JOUR
T1 - New Bregman projection methods for solving pseudo-monotone variational inequality problem
AU - Sunthrayuth, Pongsakorn
AU - Jolaoso, Lateef Olakunle
AU - Cholamjiak, Prasit
N1 - Publisher Copyright:
© 2021, Korean Society for Informatics and Computational Applied Mathematics.
PY - 2022/6
Y1 - 2022/6
N2 - In this work, we introduce two Bregman projection algorithms with self-adaptive stepsize for solving pseudo-monotone variational inequality problem in a Hilbert space. The weak and strong convergence theorems are established without the prior knowledge of Lipschitz constant of the cost operator. The convergence behavior of the proposed algorithms with various functions of the Bregman distance are presented. More so, the performance and efficiency of our methods are compared to other related methods in the literature.
AB - In this work, we introduce two Bregman projection algorithms with self-adaptive stepsize for solving pseudo-monotone variational inequality problem in a Hilbert space. The weak and strong convergence theorems are established without the prior knowledge of Lipschitz constant of the cost operator. The convergence behavior of the proposed algorithms with various functions of the Bregman distance are presented. More so, the performance and efficiency of our methods are compared to other related methods in the literature.
KW - Bregman projection
KW - Hilbert space
KW - Pseudo-monotone mapping
KW - Strong convergence
KW - Variational inequality
UR - http://www.scopus.com/inward/record.url?scp=85121390278&partnerID=8YFLogxK
U2 - 10.1007/s12190-021-01581-2
DO - 10.1007/s12190-021-01581-2
M3 - Article
AN - SCOPUS:85121390278
SN - 1598-5865
VL - 68
SP - 1565
EP - 1589
JO - Journal of Applied Mathematics and Computing
JF - Journal of Applied Mathematics and Computing
IS - 3
ER -