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

Authors Gramoz Goranci, Monika Henzinger, Mikkel Thorup

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Gramoz Goranci
Monika Henzinger
Mikkel Thorup

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Gramoz Goranci, Monika Henzinger, and Mikkel Thorup. Incremental Exact Min-Cut in Poly-logarithmic Amortized Update Time. In 24th Annual European Symposium on Algorithms (ESA 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 57, pp. 46:1-46:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


We present a deterministic incremental algorithm for exactly maintaining the size of a minimum cut with ~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/epsilon^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+epsilon)-approximation to the minimum cut. The algorithm has ~O(1) amortized update-time and constant query-time.
  • Dynamic Graph Algorithms
  • Minimum Cut
  • Edge Connectivity


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