A Computational Study of the Homogeneous Algorithm for Large-scale Convex Optimization

descriptionPublicationkeyboard_double_arrow_right Article 01 Jul 1998 English Publisher:Springer Science and Business Media LLCJournal:Computational Optimization and Applications, volume 10, pages 243-269 (issn: 0926-6003, eissn: 1573-2894,

Copyright policy )Funded by:NSF | Interior-point Algorithms..., NSF | Interior-Point Algorithms...

Authors: Andersen, Erling D.; Ye, Yinyu;

doi: 10.1023/a:1018369223322

A Computational Study of the Homogeneous Algorithm for Large-scale Convex Optimization

- Summary
- Subjects
- Metrics

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Related Organizations

Keywords

Large-scale problems in mathematical programming, homogeneous and self-dual model, Convex programming, single phase interior-point type method, smooth convex optimization, interior-point algorithms, large-scale sparse convex optimization, Quadratic programming, monotone complementarity problem

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	36
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average