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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/6826
Title: A Global and Quadratic Affine Scaling Method for Linear $L_{1}$ Problems.
Authors: Coleman, Thomas F.
Li, Yuying
Keywords: computer science
technical report
Issue Date: Jul-1989
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR89-1026
Abstract: Recently, various interior point algorithms - related to the Karmarkar algorithm - have been developed for linear programming. In this paper, we first show how this "interior point" philosophy can be adapted to the linear $l_{1}$ problem (in which there are no feasibility constraints) to yield a globally convergent algorithm. We then show that the linear algorithm can be modified to provide a globally and ultimately quadratically convergent algorithm. This modified algorithm is significantly more efficient in practice: we present numerical results to support this claim.
URI: http://hdl.handle.net/1813/6826
Appears in Collections:Computer Science Technical Reports

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