A polynomial algorithm for convex quadratic optimization subject to linear inequalities

This article proposes a polynomial-time algorithm for convex quadratic optimization subject to linear inequalities. The running time of the algorithm is polynomial in the binary size of the input data and in the logarithm of the reciprocal of the given accuracy.

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Bibliographic Details
Published inDiscrete Applied Mathematics Vol. 275; pp. 19 - 28
Main Author Chubanov, Sergei
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 31.03.2020
Elsevier BV
Subjects
Algorithms
Convex optimization
Inequalities
Linear functions
Linear programming
Optimization
Polynomials
Convex optimization
Linear programming
Online AccessGet full text
ISSN0166-218X
1872-6771
DOI10.1016/j.dam.2019.12.001

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Summary:This article proposes a polynomial-time algorithm for convex quadratic optimization subject to linear inequalities. The running time of the algorithm is polynomial in the binary size of the input data and in the logarithm of the reciprocal of the given accuracy.
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ISSN:0166-218X
1872-6771
DOI:10.1016/j.dam.2019.12.001