Improved Fixed Point Iterative Methods for Tensor Complementarity Problem

Ge Li; Jicheng Li

doi:10.1007/s10957-023-02304-2

Improved Fixed Point Iterative Methods for Tensor Complementarity Problem

Ge Li
, Jicheng Li

School of Mathematics and Statistics

Xi'an Jiaotong University

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	787-804
Number of pages	18
Journal	Journal of Optimization Theory and Applications
Volume	199
Issue number	2
DOIs	https://doi.org/10.1007/s10957-023-02304-2
State	Published - Nov 2023

Keywords

Fixed point iterative method
L-tensor
Monotone convergence
Power Lipschitz tensor
Tensor complementarity problem

Access to Document

10.1007/s10957-023-02304-2

Cite this

@article{f59e28d228bc4e76b8051f33890bc406,

title = "Improved Fixed Point Iterative Methods for Tensor Complementarity Problem",

abstract = "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.",

keywords = "Fixed point iterative method, L-tensor, Monotone convergence, Power Lipschitz tensor, Tensor complementarity problem",

author = "Ge Li and Jicheng Li",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.",

year = "2023",

month = nov,

doi = "10.1007/s10957-023-02304-2",

language = "英语",

volume = "199",

pages = "787--804",

journal = "Journal of Optimization Theory and Applications",

issn = "0022-3239",

publisher = "Springer New York",

number = "2",

}

TY - JOUR

T1 - Improved Fixed Point Iterative Methods for Tensor Complementarity Problem

AU - Li, Ge

AU - Li, Jicheng

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 -

Improved Fixed Point Iterative Methods for Tensor Complementarity Problem

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this