Improved Fixed Point Iterative Methods for Tensor Complementarity Problem

Ge Li () and Jicheng Li ()
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Ge Li: Xi’an Jiaotong University
Jicheng Li: Xi’an Jiaotong University

Journal of Optimization Theory and Applications, 2023, vol. 199, issue 2, No 13, 787-804

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

Keywords: Tensor complementarity problem; Fixed point iterative method; Power Lipschitz tensor; $$\mathcal {L}$$ L -tensor; Monotone convergence (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10957-023-02304-2

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