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Nonconvex quadratic optimization on a parallelepiped

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Abstract

An approximate combinatorial method for solving optimization problems is used to search for a global maximum of a quadratic function on a parallelepiped. Approximating functions in this method are majorants of an object function which are defined on subsets of a parallelepiped of admissible solutions. The method is based on a diagonal or block-diagonal LDL T-factorization of a matrix of an object function.

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Authors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, pr. Akad. Lavrent’eva 6, Novosibirsk, 630090, Russia

    E. A. Kotel’nikov

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  1. E. A. Kotel’nikov
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Original Russian Text © E.A. Kotel’nikov, 2008, published in Sibirskii Zhurnal Vychislitel’noi Matematiki, 2008, Vol. 11, No. 1, pp. 69–81.

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Kotel’nikov, E.A. Nonconvex quadratic optimization on a parallelepiped. Numer. Analys. Appl. 1, 58–68 (2008). https://doi.org/10.1134/S1995423908010060

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  • DOI: https://doi.org/10.1134/S1995423908010060

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