TY - JOUR
T1 - Improved Fixed Point Iterative Methods for Tensor Complementarity Problem
AU - Li, Ge
AU - Li, Jicheng
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/11
Y1 - 2023/11
N2 - In this paper, we propose two improved fixed point iterative methods for tensor complementarity problem (TCP), which decrease the number of fixed point iterations. First, based on the tensor splitting, we develop two-step fixed point iterative method and prove that this method converges to a solution of TCP. Then, we present subspace fixed point iterative method for TCP with L -tensor and this method still holds the monotone convergence property. Numerical experiments illustrate the effectiveness of our proposed methods.
AB - In this paper, we propose two improved fixed point iterative methods for tensor complementarity problem (TCP), which decrease the number of fixed point iterations. First, based on the tensor splitting, we develop two-step fixed point iterative method and prove that this method converges to a solution of TCP. Then, we present subspace fixed point iterative method for TCP with L -tensor and this method still holds the monotone convergence property. Numerical experiments illustrate the effectiveness of our proposed methods.
KW - Fixed point iterative method
KW - L-tensor
KW - Monotone convergence
KW - Power Lipschitz tensor
KW - Tensor complementarity problem
UR - https://www.scopus.com/pages/publications/85172896946
U2 - 10.1007/s10957-023-02304-2
DO - 10.1007/s10957-023-02304-2
M3 - 文章
AN - SCOPUS:85172896946
SN - 0022-3239
VL - 199
SP - 787
EP - 804
JO - Journal of Optimization Theory and Applications
JF - Journal of Optimization Theory and Applications
IS - 2
ER -