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Planar Network Diversion

Authors Matthias Bentert, Pål Grønås Drange , Fedor V. Fomin , Steinar Simonnes

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Subject Classification

ACM Subject Classification
  • Mathematics of computing → Paths and connectivity problems
  • Mathematics of computing → Graphs and surfaces
  • Mathematics of computing → Graph algorithms
  • Theory of computation → Streaming, sublinear and near linear time algorithms
  • Theory of computation → Graph algorithms analysis
Keywords
  • Minimal cuts
  • Bridges
  • Network interdiction
  • Algorithm engineering

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Abstract

Network Diversion is a graph problem that has been extensively studied in both the network-analysis and operations-research communities as a measure of how robust a network is against adversarial disruption. In Network Diversion we want to enforce all s-t-paths through a specific edge b by removing edges from G. This problem is especially well motivated in transportation networks, which are often assumed to be planar. Motivated by this and recent theoretical advances for Network Diversion on planar input graphs, we develop a fast O(n log n) time algorithm and present a practical implementation of this algorithm that is able to solve instances with millions of vertices in a matter of seconds.

Cite As Get BibTex

Matthias Bentert, Pål Grønås Drange, Fedor V. Fomin, and Steinar Simonnes. Planar Network Diversion. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 6:1-6:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.SEA.2025.6

Author Details

Matthias Bentert
  • University of Bergen, Norway
Pål Grønås Drange
  • University of Bergen, Norway
Fedor V. Fomin
  • University of Bergen, Norway
Steinar Simonnes
  • University of Bergen, Norway

Funding

  • Bentert, Matthias: Supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 819416).
  • Fomin, Fedor V.: Supported by the Research Council of Norway, Beyond Worst-Case Analysis in Algorithms (grant agreement no. 314528).

Acknowledgements

We sincerely thank Petr Golovach and Tuukka Korhonen for their insightful discussions in the early stages of this work, which helped shape the development of the algorithm presented in this paper.

Supplementary Materials

References

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