Tensor Z-eigenvalue complementarity problems

Meilan Zeng ()
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Meilan Zeng: Hubei Engineering University

Computational Optimization and Applications, 2021, vol. 78, issue 2, No 8, 559-573

Abstract: Abstract This paper studies tensor Z-eigenvalue complementarity problems. We formulate the tensor Z-eigenvalue complementarity problem as constrained polynomial optimization, and propose a semidefinite relaxation algorithm for solving the complementarity Z-eigenvalues of tensors. For every tensor that has finitely many complementarity Z-eigenvalues, we can compute all of them and show that our algorithm has the asymptotic and finite convergence. Numerical experiments indicate the efficiency of the proposed method.

Keywords: Complementarity Z-eigenvalue; Semidefinite relaxation; Asymptotic convergence; Finite convergence; 15A18; 65K10; 90C22 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10589-020-00248-1

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