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Improved Fixed Point Iterative Methods for Tensor Complementarity Problem

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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 \(\mathcal { L}\)-tensor and this method still holds the monotone convergence property. Numerical experiments illustrate the effectiveness of our proposed methods.

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We do not analyze or generate any datasets, because our work proceeds within a theoretical and mathematical approach.

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Acknowledgements

The work was supported by National Natural Science Foundation of China (12171384).

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Authors and Affiliations

  1. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, 710049, China

    Ge Li & Jicheng Li

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  1. Ge Li
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  2. Jicheng Li
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Correspondence to Jicheng Li.

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Communicated by Liqun Qi.

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Li, G., Li, J. Improved Fixed Point Iterative Methods for Tensor Complementarity Problem. J Optim Theory Appl 199, 787–804 (2023). https://doi.org/10.1007/s10957-023-02304-2

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  • DOI: https://doi.org/10.1007/s10957-023-02304-2

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