A semidefinite relaxation method for second-order cone polynomial complementarity problems
This paper discusses how to compute all real solutions of the second-order cone tensor complementarity problem when there are finitely many ones. For this goal, we first formulate the second-order cone tensor complementarity problem as two polynomial optimization problems. Based on the reformulation...
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| Veröffentlicht in: | Computational optimization and applications 2020-04, Vol.75 (3), p.629-647 |
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| creator | Cheng, Lulu Zhang, Xinzhen |
| description | This paper discusses how to compute all real solutions of the second-order cone tensor complementarity problem when there are finitely many ones. For this goal, we first formulate the second-order cone tensor complementarity problem as two polynomial optimization problems. Based on the reformulation, a semidefinite relaxation method is proposed by solving a finite number of semidefinite relaxations with some assumptions. Numerical experiments are given to show the efficiency of the method. |
| doi_str_mv | 10.1007/s10589-019-00162-1 |
| format | Article |
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For this goal, we first formulate the second-order cone tensor complementarity problem as two polynomial optimization problems. Based on the reformulation, a semidefinite relaxation method is proposed by solving a finite number of semidefinite relaxations with some assumptions. 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| source | EBSCOhost Business Source Complete; SpringerLink Journals - AutoHoldings |
| subjects | Convex and Discrete Geometry Management Science Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Polynomials Relaxation method (mathematics) Statistics Tensors |
| title | A semidefinite relaxation method for second-order cone polynomial complementarity problems |
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