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Random-Edge Is Slower Than Random-Facet on Abstract Cubes

机译:随机边缘比抽象立方体上的随机面更慢

摘要

Random-Edge and Random-Facet are two very natural randomized pivoting rules for the simplex algorithm. The behavior of Random-Facet is fairly well understood. It performs an expected sub-exponential number of pivoting steps on any linear program, or more generally, on any Acyclic Unique Sink Orientation (AUSO) of an arbitrary polytope, making it the fastest known pivoting rule for the simplex algorithm. The behavior of Random-Edge is much less understood. We show that in the AUSO setting, Random-Edge is slower than Random-Facet. To do that, we construct AUSOs of the n-dimensional hypercube on which Random-Edge performs an expected number of 2^{Omega(sqrt(n*log(n)))} steps. This improves on a 2^{Omega(sqrt^3(n))} lower bound of Matoušek and Szabó. As Random-Facet performs an expected number of 2^{O(sqrt(n)} steps on any n-dimensional AUSO, this established our result. Improving our 2^{Omega(sqrt(n*log(n)))} lower bound seems to require radically new techniques.
机译:对于单形算法,Random-Edge和Random-Facet是两个非常自然的随机枢转规则。 Random-Facet的行为已被很好地理解。它在任意线性程序或更一般地在任意多面体的任何非循环唯一接收器方向(AUSO)上执行预期的次指数级旋转步骤,使其成为最快的已知单纯形算法旋转规则。对Random-Edge的行为知之甚少。我们表明,在AUSO设置中,Random-Edge比Random-Facet慢。为此,我们构造了n维超立方体的AUSO,Random-Edge在AUSO上执行了预期的2 ^ {Omega(sqrt(n * log(n)))}个步骤。这会提高Matoušek和Szabó的2 ^ {Omega(sqrt ^ 3(n))}下限。由于Random-Facet在任何n维AUSO上执行了预期的2 ^ {O(sqrt(n)}个步数,因此建立了我们的结果。改进了2 ^ {Omega(sqrt(n * log(n)))}下限似乎需要彻底的新技术。

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