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A Linear Programming Reformulation of the Standard Quadratic Optimization Problem

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  • de Klerk, E.

    (Tilburg University, Center For Economic Research)

  • Pasechnik, D.V.

    (Tilburg University, Center For Economic Research)

Abstract

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Suggested Citation

  • de Klerk, E. & Pasechnik, D.V., 2005. "A Linear Programming Reformulation of the Standard Quadratic Optimization Problem," Discussion Paper 2005-24, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:f63bfe23-904e-4d7a-8677-88492a806556
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    File URL: https://pure.uvt.nl/ws/portalfiles/portal/773232/24.pdf
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    References listed on IDEAS

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    1. NESTEROV, Yu, 2003. "Random walk in a simplex and quadratic optimization over convex polytopes," LIDAM Discussion Papers CORE 2003071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Jean B. Lasserre, 2002. "Semidefinite Programming vs. LP Relaxations for Polynomial Programming," Mathematics of Operations Research, INFORMS, vol. 27(2), pages 347-360, May.
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    Cited by:

    1. X. J. Zheng & X. L. Sun & D. Li, 2010. "Separable Relaxation for Nonconvex Quadratic Integer Programming: Integer Diagonalization Approach," Journal of Optimization Theory and Applications, Springer, vol. 146(2), pages 463-489, August.
    2. Xiaolong Kuang & Luis F. Zuluaga, 2018. "Completely positive and completely positive semidefinite tensor relaxations for polynomial optimization," Journal of Global Optimization, Springer, vol. 70(3), pages 551-577, March.
    3. Bomze, Immanuel M., 2012. "Copositive optimization – Recent developments and applications," European Journal of Operational Research, Elsevier, vol. 216(3), pages 509-520.

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