Exponential Lower Bounds for History-Based Simplex Pivot Rules on Abstract Cubes

Author Antonis Thomas

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Antonis Thomas

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Antonis Thomas. Exponential Lower Bounds for History-Based Simplex Pivot Rules on Abstract Cubes. In 25th Annual European Symposium on Algorithms (ESA 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 87, pp. 69:1-69:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


The behavior of the simplex algorithm is a widely studied subject. Specifically, the question of the existence of a polynomial pivot rule for the simplex algorithm is of major importance. Here, we give exponential lower bounds for three history-based pivot rules. Those rules decide their next step based on memory of the past steps. In particular, we study Zadeh's least entered rule, Johnson's least-recently basic rule and Cunningham's least-recently considered (or round-robin) rule. We give exponential lower bounds on Acyclic Unique Sink Orientations of the abstract cube, for all of these pivot rules. For Johnson's rule our bound is the first superpolynomial one in any context; for Zadeh's it is the first one for AUSO. Those two are our main results.
  • pivot rule
  • lower bound
  • exponential
  • unique sink orientation
  • zadeh


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