A quadratic programming algorithm for large and sparse problems
Miroslav Tůma (1991)
Kybernetika
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Miroslav Tůma (1991)
Kybernetika
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D. Den Hertog, C. Roos, T. Terlaky (1994)
RAIRO - Operations Research - Recherche Opérationnelle
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Predrag Stanimirović, Svetozar Rančić (1999)
The Yugoslav Journal of Operations Research
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Richard Andrášik (2013)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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Nonlinear rescaling is a tool for solving large-scale nonlinear programming problems. The primal-dual nonlinear rescaling method was used to solve two quadratic programming problems with quadratic constraints. Based on the performance of primal-dual nonlinear rescaling method on testing problems, the conclusions about setting up the parameters are made. Next, the connection between nonlinear rescaling methods and self-concordant functions is discussed and modified logarithmic barrier...
Y. Q. Bai, F. Y. Wang, X. W. Luo (2010)
RAIRO - Operations Research
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In this paper we propose a primal-dual interior-point algorithm for convex quadratic semidefinite optimization problem. The search direction of algorithm is defined in terms of a matrix function and the iteration is generated by full-Newton step. Furthermore, we derive the iteration bound for the algorithm with small-update method, namely, ( log ), which is best-known bound so far.
Nebojša V. Stojković (2001)
The Yugoslav Journal of Operations Research
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