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Revisiting a Cutting Plane Method for Perfect Matchings
[article]
2019
arXiv
pre-print
In 2016, Chandrasekaran, Végh, and Vempala published a method to solve the minimum-cost perfect matching problem on an arbitrary graph by solving a strictly polynomial number of linear programs. However, their method requires a strong uniqueness condition, which they imposed by using perturbations of the form c(i)=c_0(i)+2^-i. On large graphs (roughly m>100), these perturbations lead to cost values that exceed the precision of floating-point formats used by typical linear programming solvers
arXiv:1908.10989v1
fatcat:g7ky5oxvhbhwzib6sva4t75hem