A semidefinite relaxation method for second-order cone tensor eigenvalue complementarity problems

Lulu Cheng (), Xinzhen Zhang () and Guyan Ni ()
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Lulu Cheng: Tianjin University
Xinzhen Zhang: Tianjin University
Guyan Ni: National University of Defense Technology

Journal of Global Optimization, 2021, vol. 79, issue 3, No 8, 715-732

Abstract: Abstract This paper discusses second-order cone tensor eigenvalue complementarity problem. We reformulate second-order cone tensor eigenvalue complementarity problem as two constrained polynomial optimizations. For these two reformulated optimizations, Lasserre-type semidefinite relaxation methods are proposed to compute all second-order cone tensor complementarity eigenpairs. The proposed algorithms terminate when there are finitely many second-order cone complementarity eigenvalues. Numerical examples are reported to show the efficiency of the proposed algorithms.

Keywords: Second-order cone; Tensor eigenvalue complementarity; Semidefinite relaxation; 15A18; 15A69; 90C22; 90C33 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10898-020-00954-4

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