A weighted full-Newton step primal-dual interior point algorithm for convex quadratic optimization

In this paper a new weighted short-step primal-dual interior point algorithm to solve convex quadratic optimization (CQO) problems. The algorithm uses at each interior iteration afull-Newton step and the strategy of the central to obtain an epsilon-optimal solution of CQO. The algorithm yields the b...

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Veröffentlicht in:Statistics, optimization & information computing Jg. 2; H. 1; S. 21
1. Verfasser: Mohamed, Achache
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hong Kong International Academic Press (Hong Kong) 2014
Schlagworte:
Algorithms
Optimization
Queuing theory
ISSN:2311-004X, 2310-5070
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Zusammenfassung:In this paper a new weighted short-step primal-dual interior point algorithm to solve convex quadratic optimization (CQO) problems. The algorithm uses at each interior iteration afull-Newton step and the strategy of the central to obtain an epsilon-optimal solution of CQO. The algorithm yields the best currently best known theoretical complexity bound namely O(\sqrt(n) log n/epsilon).
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2311-004X
2310-5070
DOI:10.19139/soic.v2i1.21