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arXiv · 1611.06500

Incremental Exact Min-Cut in Poly-logarithmic Amortized Update Time

Gramoz Goranci·Monika Henzinger·Mikkel Thorup
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Abstract

We present a deterministic incremental algorithm for \textit{exactly} maintaining the size of a minimum cut with $\widetilde{O}(1)$ amortized time per edge insertion and $O(1)$ query time. This result partially answers an open question posed by Thorup [Combinatorica 2007]. It also stays in sharp contrast to a polynomial conditional lower-bound for the fully-dynamic weighted minimum cut problem. Our algorithm is obtained by combining a recent sparsification technique of Kawarabayashi and Thorup [STOC 2015] and an exact incremental algorithm of Henzinger [J. of Algorithm 1997]. We also study space-efficient incremental algorithms for the minimum cut problem. Concretely, we show that there exists an ${O}(n\log n/\varepsilon^2)$ space Monte-Carlo algorithm that can process a stream of edge insertions starting from an empty graph, and with high probability, the algorithm maintains a $(1+\varepsilon)$-approximation to the minimum cut. The algorithm has $\widetilde{O}(1)$ amortized update-time and constant query-time.

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Gramoz Goranci, Monika Henzinger, Mikkel Thorup. 2016-11-20. Incremental Exact Min-Cut in Poly-logarithmic Amortized Update Time. https://doi.org/10.4230/lipics.esa.2016.46

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