SDP relaxation algorithms for $$\mathbf {P}(\mathbf {P}_0)$$P(P0)-tensor detection
Xiao Wang (),
Xinzhen Zhang () and
Guangming Zhou ()
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Xiao Wang: Tianjin University
Xinzhen Zhang: Tianjin University
Guangming Zhou: Xiangtan University
Computational Optimization and Applications, 2020, vol. 75, issue 3, No 7, 739-752
Abstract:
Abstract $$\mathbf {P}$$P-tensor and $$\mathbf {P}_0$$P0-tensor are introduced in tensor complementarity problem, which have wide applications in game theory. In this paper, we establish SDP relaxation algorithms for detecting $$\mathbf {P}(\mathbf {P}_0)$$P(P0)-tensor. We first reformulate $$\mathbf {P}(\mathbf {P}_0)$$P(P0)-tensor detection problem as polynomial optimization problems. Then we propose the SDP relaxation algorithms for solving the reformulated polynomial optimization problems. Numerical examples are reported to show the efficiency of the proposed algorithms.
Keywords: Tensor; $$\mathbf {P}$$ P -tensor; $$\mathbf {P}_0$$ P 0 -tensor; Lasserre’s hierarchy; Semidefinite program; 15A18; 15A69; 90C22 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10589-019-00145-2
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