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Global quadratic optimization on the sets with simplex structure

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  • NESTEROV, Yurii

    (Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCL), 1348 Louvain la Neuve, Belgium)

Abstract

In the first part of this paper we prove that the global quadratic optimization problem over a simplex can be solved with a constant relative accuracy. In the second part we consider some natural extensions of the result.

Suggested Citation

  • NESTEROV, Yurii, 1999. "Global quadratic optimization on the sets with simplex structure," LIDAM Discussion Papers CORE 1999015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:1999015
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    File URL: https://sites.uclouvain.be/core/publications/coredp/coredp1999.html
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    References listed on IDEAS

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    1. 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).
    2. NESTEROV, Yurii, 1997. "Quality of semidefinite relaxation for nonconvex quadratic optimization," LIDAM Discussion Papers CORE 1997019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. James Chok & Geoffrey M. Vasil, 2023. "Convex optimization over a probability simplex," Papers 2305.09046, arXiv.org.
    2. Muhammad Faisal Iqbal & Faizan Ahmed, 2022. "Approximation Hierarchies for the Copositive Tensor Cone and Their Application to the Polynomial Optimization over the Simplex," Mathematics, MDPI, vol. 10(10), pages 1-17, May.
    3. 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).

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