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The Unweighted and Weighted Reverse Shortest Path Problem for Disk Graphs

Authors Haim Kaplan , Matthew J. Katz , Rachel Saban, Micha Sharir



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Author Details

Haim Kaplan
  • School of Computer Science, Tel Aviv University, Israel
Matthew J. Katz
  • Department of Computer Science, Ben Gurion University, Beer-Sheva, Israel
Rachel Saban
  • Department of Computer Science, Ben Gurion University, Beer-Sheva, Israel
Micha Sharir
  • School of Computer Science, Tel Aviv University, Israel

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Haim Kaplan, Matthew J. Katz, Rachel Saban, and Micha Sharir. The Unweighted and Weighted Reverse Shortest Path Problem for Disk Graphs. In 31st Annual European Symposium on Algorithms (ESA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 274, pp. 67:1-67:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.ESA.2023.67

Abstract

We study the reverse shortest path problem on disk graphs in the plane. In this problem we consider the proximity graph of a set of n disks in the plane of arbitrary radii: In this graph two disks are connected if the distance between them is at most some threshold parameter r. The case of intersection graphs is a special case with r = 0. We give an algorithm that, given a target length k, computes the smallest value of r for which there is a path of length at most k between some given pair of disks in the proximity graph. Our algorithm runs in O^*(n^{5/4}) randomized expected time, which improves to O^*(n^{6/5}) for unit disk graphs, where all the disks have the same radius. Our technique is robust and can be applied to many variants of the problem. One significant variant is the case of weighted proximity graphs, where edges are assigned real weights equal to the distance between the disks or between their centers, and k is replaced by a target weight w. In other variants, we want to optimize a parameter different from r, such as a scale factor of the radii of the disks. The main technique for the decision version of the problem (determining whether the graph with a given r has the desired property) is based on efficient implementations of BFS (for the unweighted case) and of Dijkstra’s algorithm (for the weighted case), using efficient data structures for maintaining the bichromatic closest pair for certain bicliques and several distance functions. The optimization problem is then solved by combining the resulting decision procedure with enhanced variants of the interval shrinking and bifurcation technique of [R. Ben Avraham et al., 2015].

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
Keywords
  • Computational geometry
  • geometric optimization
  • disk graphs
  • BFS
  • Dijkstra’s algorithm
  • reverse shortest path

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References

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