Geometric random edge

成果类型:
Article
署名作者:
Eisenbrand, Friedrich; Vempala, Santosh
署名单位:
Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University System of Georgia; Georgia Institute of Technology
刊物名称:
MATHEMATICAL PROGRAMMING
ISSN/ISSBN:
0025-5610
DOI:
10.1007/s10107-016-1089-0
发表日期:
2017
页码:
325-339
关键词:
simplex-algorithm polynomial algorithm linear-programs random-walks bounds time
摘要:
We show that a variant of the random-edge pivoting rule results in a strongly polynomial time simplex algorithm for linear programs , whose constraint matrix A satisfies a geometric property introduced by Brunsch and Roglin: The sine of the angle of a row of A to a hyperplane spanned by other rows of A is at least . This property is a geometric generalization of A being integral and each sub-determinant of A being bounded by in absolute value. In this case . In particular, linear programs defined by totally unimodular matrices are captured in this framework. Here and Dyer and Frieze previously described a strongly polynomial-time randomized simplex algorithm for linear programs with A totally unimodular. The expected number of pivots of the simplex algorithm is polynomial in the dimension and and independent of the number of constraints of the linear program. Our main result can be viewed as an algorithmic realization of the proof of small diameter for such polytopes by Bonifas et al., using the ideas of Dyer and Frieze.
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