Enhancing RLT-based relaxations for polynomial programming problems via a new class of v-semidefinite cuts
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Bibliographic InfoArticle provided by Springer in its journal Computational Optimization and Applications.
Volume (Year): 52 (2012)
Issue (Month): 2 (June)
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Web page: http://www.springer.com/math/journal/10589
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- Samuel Burer & Dieter Vandenbussche, 2009. "Globally solving box-constrained nonconvex quadratic programs with semidefinite-based finite branch-and-bound," Computational Optimization and Applications, Springer, vol. 43(2), pages 181-195, June.
- Kojima, Masakazu & Tuncel, Levent, 2002. "On the finite convergence of successive SDP relaxation methods," European Journal of Operational Research, Elsevier, vol. 143(2), pages 325-341, December.
- Helmberg, C., 2002. "Semidefinite programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 461-482, March.
- Evrim Dalkiran & Hanif Sherali, 2013. "Theoretical filtering of RLT bound-factor constraints for solving polynomial programming problems to global optimality," Journal of Global Optimization, Springer, vol. 57(4), pages 1147-1172, December.
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