Infeasible interior-point methods for linear optimization based on large neighborhood
Journal Article
(2015)
Author(s)
A. Asadi (TU Delft - Algorithmics)
C. Roos (TU Delft - Discrete Mathematics and Optimization)
Research Group
Algorithmics
DOI related publication
https://doi.org/10.1007/s10957-015-0826-5
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https://resolver.tudelft.nl/uuid:a2cfc73e-8660-4cab-bcb9-3478d6ef6d87
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Publication Year
2015
Language
English
Research Group
Algorithmics
Issue number
2
Volume number
170
Pages (from-to)
1-29
Abstract
In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortunately, despite its good numerical behavior, the theoretical convergence rate of our algorithm is worse up to square root of problem dimension.
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