On Long Step Path Following and SUMT for Linear and Quadratic Programming

We consider a long step barrier algorithm for the minimization of a convex quadratic objective subject to linear inequality constraints. The algorithm is a dual version of a method developed by Anstreicher et al. [Algorithmica, 10 (1993), pp. 365-382], and requires $O ( nL )$ or $O( \sqrt{n} L )$ it...

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Vydáno v:SIAM journal on optimization Ročník 6; číslo 1; s. 33 - 46
Hlavní autor: Anstreicher, Kurt M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Philadelphia Society for Industrial and Applied Mathematics 01.02.1996
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ISSN:1052-6234, 1095-7189
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Shrnutí:We consider a long step barrier algorithm for the minimization of a convex quadratic objective subject to linear inequality constraints. The algorithm is a dual version of a method developed by Anstreicher et al. [Algorithmica, 10 (1993), pp. 365-382], and requires $O ( nL )$ or $O( \sqrt{n} L )$ iterations to solve a problem with n constraints, depending on how the barrier parameter is reduced. As a corollary of our analysis we demonstrate that the classical SUMT algorithm, exactly as implemented in 1968, solves linear and quadratic programs in $O( \sqrt{n} L\log L )$ iterations, with proper initialization and choice of parameters.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:1052-6234
1095-7189
DOI:10.1137/0806003