Numerical Analysis and Applications

, Volume 3, Issue 1, pp 17–24 | Cite as

applying a reduced gradient in quadratic programming

  • E. A. Kotel’nikov


This paper considers specific aspects of implementing an algorithm for solving problems of quadratic programming, which is based on a reduced gradient method. In the subspace of superbasis variables, minimization is carried out by a conjugate gradient method. Some examples of solving test problems are given.

Key words

quadratic programming reduced gradient conjugate gradient basis superbasis 


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Copyright information

© Pleiades Publishing, Ltd. 2010

Authors and Affiliations

  • E. A. Kotel’nikov
    • 1
  1. 1.Institute of Computational Mathematics and Mathematical Geophysics, Siberian BranchRussian Academy of SciencesNovosibirskRussia

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