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Semidefinite relaxation and nonconvex quadratic optimization

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  • NESTEROV, Yurii

    (Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCL), Louvain la Neuve, Belgium)

Abstract

In this paper we consider the semidefinite relaxation of some global optimization problems. We prove that in some cases this relaxation provides us with a constant relative accuracy estimate for the exact solution.

Suggested Citation

  • NESTEROV, Yurii, 1997. "Semidefinite relaxation and nonconvex quadratic optimization," LIDAM Discussion Papers CORE 1997044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:1997044
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    File URL: https://sites.uclouvain.be/core/publications/coredp/coredp1997.html
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    Cited by:

    1. Nikhil Bhat & Vivek F. Farias & Ciamac C. Moallemi & Deeksha Sinha, 2020. "Near-Optimal A-B Testing," Management Science, INFORMS, vol. 66(10), pages 4477-4495, October.
    2. Lei-Hong Zhang & Li-Zhi Liao, 2012. "An alternating variable method for the maximal correlation problem," Journal of Global Optimization, Springer, vol. 54(1), pages 199-218, September.
    3. NESTEROV, Yurii, 1998. "Global quadratic optimization via conic relaxation," LIDAM Discussion Papers CORE 1998060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Yuning Yang & Qingzhi Yang, 2012. "On solving biquadratic optimization via semidefinite relaxation," Computational Optimization and Applications, Springer, vol. 53(3), pages 845-867, December.
    5. F. Rendl, 2016. "Semidefinite relaxations for partitioning, assignment and ordering problems," Annals of Operations Research, Springer, vol. 240(1), pages 119-140, May.

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