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Paper

#### An Integer Interior Point Method for Min-Cost Flow Using Arc Contractions and Deletions

##### MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons118120

Becker,  Ruben
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44737

Karrenbauer,  Andreas
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45021

Mehlhorn,  Kurt
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

##### Locator
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##### Fulltext (public)

arXiv:1612.04689.pdf
(Preprint), 278KB

##### Supplementary Material (public)
There is no public supplementary material available
##### Citation

Becker, R., Karrenbauer, A., & Mehlhorn, K. (2016). An Integer Interior Point Method for Min-Cost Flow Using Arc Contractions and Deletions. Retrieved from http://arxiv.org/abs/1612.04689.

Cite as: http://hdl.handle.net/11858/00-001M-0000-002C-5714-E
##### Abstract
We present an interior point method for the min-cost flow problem that uses arc contractions and deletions to steer clear from the boundary of the polytope when path-following methods come too close. We obtain a randomized algorithm running in expected $\tilde O( m^{3/2} )$ time that only visits integer lattice points in the vicinity of the central path of the polytope. This enables us to use integer arithmetic like classical combinatorial algorithms typically do. We provide explicit bounds on the size of the numbers that appear during all computations. By presenting an integer arithmetic interior point algorithm we avoid the tediousness of floating point error analysis and achieve a method that is guaranteed to be free of any numerical issues. We thereby eliminate one of the drawbacks of numerical methods in contrast to combinatorial min-cost flow algorithms that still yield the most efficient implementations in practice, despite their inferior worst-case time complexity.