Using a Geometric Lens to Find k Disjoint Shortest Paths

Authors Matthias Bentert, André Nichterlein , Malte Renken , Philipp Zschoche



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Matthias Bentert
  • Faculty IV, Algorithmics and Computational Complexity, Technische Universität Berlin, Germany
André Nichterlein
  • Faculty IV, Algorithmics and Computational Complexity, Technische Universität Berlin, Germany
Malte Renken
  • Faculty IV, Algorithmics and Computational Complexity, Technische Universität Berlin, Germany
Philipp Zschoche
  • Faculty IV, Algorithmics and Computational Complexity, Technische Universität Berlin, Germany

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Matthias Bentert, André Nichterlein, Malte Renken, and Philipp Zschoche. Using a Geometric Lens to Find k Disjoint Shortest Paths. In 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 198, pp. 26:1-26:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.ICALP.2021.26

Abstract

Given an undirected n-vertex graph and k pairs of terminal vertices (s_1,t_1), …, (s_k,t_k), the k-Disjoint Shortest Paths (k-DSP) problem asks whether there are k pairwise vertex-disjoint paths P_1, …, P_k such that P_i is a shortest s_i-t_i-path for each i ∈ [k]. Recently, Lochet [SODA '21] provided an algorithm that solves k-DSP in n^{O(k^{5^k})} time, answering a 20-year old question about the computational complexity of k-DSP for constant k. On the one hand, we present an improved O(kn^{16k ⋅ k! + k + 1})-time algorithm based on a novel geometric view on this problem. For the special case k = 2, we show that the running time can be further reduced to O(nm) by small modifications of the algorithm and a further refined analysis. On the other hand, we show that k-DSP is W[1]-hard with respect to k, showing that the dependency of the degree of the polynomial running time on the parameter k is presumably unavoidable.

Subject Classification

ACM Subject Classification
  • Theory of computation → Graph algorithms analysis
Keywords
  • graph algorithms
  • dynamic programming
  • W[1]-hardness
  • geometry

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References

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