Geodesic
Applying a~reduced gradient in the quadratic programming
Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 13 (2010) no. 1, pp. 23-31

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This paper considers specific aspects of implementing the algorithm for solving problems of the quadratic programming, which is based on the reduced gradient method. In the current subspace of the superbasis variables, minimization is carried out by the conjugate gradient method. Some examples of solution of test problems are given. 
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     author = {E. A. Kotel'nikov},
     title = {Applying a~reduced gradient in the quadratic programming},
     journal = {Sibirskij \v{z}urnal vy\v{c}islitelʹnoj matematiki},
     pages = {23--31},
     publisher = {mathdoc},
     volume = {13},
     number = {1},
     year = {2010},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/SJVM_2010_13_1_a2/}
}
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E. A. Kotel'nikov. Applying a~reduced gradient in the quadratic programming. Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 13 (2010) no. 1, pp. 23-31. http://geodesic.mathdoc.fr/item/SJVM_2010_13_1_a2/