The simplex algorithm in dimension three

Volker Kaibel*, Rafael Mechtel, Micha Sharir, Günter M. Ziegler

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We investigate the worst-case behavior of the simplex algorithm on linear programs with three variables, that is, on 3-dimensional simple polytopes. Among the pivot rules that we consider, the "random edge" rule yields the best asymptotic behavior as well as the most complicated analysis. All other rules turn out to be much easier to study, but also produce worse results: Most of them show essentially worst-possible behavior; this includes both Kalai's "random-facet" rule, which without dimension restriction is known to be subexponential, and Zadeh's deterministic history-dependent rule, for which no nonpolynomial instances in general dimensions have been found so far.

Original languageEnglish
Pages (from-to)475-497
Number of pages23
JournalSIAM Journal on Computing
Volume34
Issue number2
DOIs
StatePublished - 2005

Keywords

  • Linear programming
  • Linearity coefficient
  • Pivot rule
  • Random edge

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