Solving Totally Unimodular LPs with the Shadow Vertex Algorithm

Authors Tobias Brunsch, Anna Großwendt, Heiko Röglin



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Tobias Brunsch
Anna Großwendt
Heiko Röglin

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Tobias Brunsch, Anna Großwendt, and Heiko Röglin. Solving Totally Unimodular LPs with the Shadow Vertex Algorithm. In 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 30, pp. 171-183, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)
https://doi.org/10.4230/LIPIcs.STACS.2015.171

Abstract

We show that the shadow vertex simplex algorithm can be used to solve linear programs in strongly polynomial time with respect to the number n of variables, the number m of constraints, and 1/\delta, where \delta is a parameter that measures the flatness of the vertices of the polyhedron. This extends our recent result that the shadow vertex algorithm finds paths of polynomial length (w.r.t. n, m, and 1/delta) between two given vertices of a polyhedron [4]. Our result also complements a recent result due to Eisenbrand and Vempala [6] who have shown that a certain version of the random edge pivot rule solves linear programs with a running time that is strongly polynomial in the number of variables n and 1/\delta, but independent of the number m of constraints. Even though the running time of our algorithm depends on m, it is significantly faster for the important special case of totally unimodular linear programs, for which 1/delta\le n and which have only O(n^2) constraints.
Keywords
  • linear optimization
  • simplex algorithm
  • shadow vertex method

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References

  1. Nicolas Bonifas, Marco Di Summa, Friedrich Eisenbrand, Nicolai Hähnle, and Martin Niemeier. On sub-determinants and the diameter of polyhedra. In Proceedings of the 28th ACM Symposium on Computational Geometry (SoCG), pages 357-362, 2012. Google Scholar
  2. Karl Heinz Borgwardt. A probabilistic analysis of the simplex method. Springer-Verlag New York, Inc., New York, NY, USA, 1986. Google Scholar
  3. Tobias Brunsch, Anna Großwendt, and Heiko Röglin. Solving totally unimodular LPs with the shadow vertex algorithm. CoRR, abs/1412.5381, 2014. Google Scholar
  4. Tobias Brunsch and Heiko Röglin. Finding short paths on polytopes by the shadow vertex algorithm. In Proceedings of the 40th International Colloquium on Automata, Languages and Programming (ICALP), pages 279-290, 2013. Google Scholar
  5. Martin E. Dyer and Alan M. Frieze. Random walks, totally unimodular matrices, and a randomised dual simplex algorithm. Mathematical Programming, 64:1-16, 1994. Google Scholar
  6. Friedrich Eisenbrand and Santosh Vempala. Geometric random edge. CoRR, abs/1404.1568, 2014. Google Scholar
  7. I. Heller. On linear systems with integral valued solutions. Pacific Journal of Mathematics, 7(3):1351-1364, 1957. Google Scholar
  8. Daniel A. Spielman and Shang-Hua Teng. Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time. Journal of the ACM, 51(3):385-463, 2004. Google Scholar
  9. Éva Tardos. A strongly polynomial algorithm to solve combinatorial linear programs. Operations Research, 34(2):250-256, 1986. Google Scholar
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