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

被引：0
作者：
Lulu Cheng
Xinzhen Zhang
Guyan Ni
机构：
[1] Tianjin University,School of Mathematics
[2] National University of Defense Technology,Department of Mathematics
来源：
Journal of Global Optimization | 2021年 / 79卷
关键词：
Second-order cone; Tensor eigenvalue complementarity; Semidefinite relaxation; 15A18; 15A69; 90C22; 90C33;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：715 / 732
页数：17
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