On some efficient interior point methods for nonlinear convex programming

K.O. Kortanek; Florian Potra; Yinyu Ye

doi:10.1016/0024-3795(91)90274-Z

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On some efficient interior point methods for nonlinear convex programming

Journal article

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Peer reviewed

On some efficient interior point methods for nonlinear convex programming

K.O. Kortanek, Florian Potra and Yinyu Ye

Linear algebra and its applications, Vol.152(C), pp.169-189

07/01/1991

DOI: 10.1016/0024-3795(91)90274-Z

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Abstract

We introduce two interior point algorithms for minimizing a convex function subject to linear constraints. Our algorithms require the solution of a nonlinear system of equations at each step. We show that if sufficiently good approximations to the solutions of the nonlinear systems can be found, then the primal-dual gap becomes less that ε in O( n |lnε|) steps, where n is the number of variables.

Details

Title: Subtitle: On some efficient interior point methods for nonlinear convex programming
Creators: K.O. Kortanek - University of Iowa
Florian Potra - University of Iowa
Yinyu Ye - University of Iowa
Resource Type: Journal article
Publication Details: Linear algebra and its applications, Vol.152(C), pp.169-189
DOI: 10.1016/0024-3795(91)90274-Z
ISSN: 0024-3795
eISSN: 1873-1856
Publisher: Elsevier Inc
Number of pages: 21
Language: English
Date published: 07/01/1991
Academic Unit: Business Analytics
Record Identifier: 9984963111502771

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