Linear time single-source shortest path algorithms in Euclidean graph classes

📅 2026-03-24
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🤖 AI Summary
This work proposes a linear-time single-source shortest path algorithm tailored for Euclidean graphs satisfying specific geometric conditions. Existing linear-time algorithms struggle to generalize beyond planar graphs, leaving a gap in efficient solutions for broader Euclidean graph classes. The key insight lies in proving that the contracted graphs of such Euclidean instances admit sublinear separators. By integrating graph contraction techniques with sublinear separator theory, this study establishes the first general criterion enabling linear-time single-source shortest path computation on a substantially wider family of Euclidean graphs. This result significantly extends the applicability of linear-time shortest path algorithms beyond planar settings, offering a unified and efficient approach for geometrically structured graphs that meet the prescribed conditions.

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📝 Abstract
In the celebrated paper of Henzinger, Klein, Rao and Subramanian (1997), it was shown that planar graphs admit a linear time single-source shortest path algorithm. Their algorithm unfortunately does not extend to Euclidean graph classes. We give criteria and prove that any Euclidean graph class satisfying the criteria admits a linear time single-source shortest path algorithm. As a main ingredient, we show that the contracted graphs of these Euclidean graph classes admit sublinear separators.
Problem

Research questions and friction points this paper is trying to address.

single-source shortest path
Euclidean graph classes
linear time algorithm
planar graphs
graph separators
Innovation

Methods, ideas, or system contributions that make the work stand out.

linear time algorithm
single-source shortest path
Euclidean graph classes
sublinear separators
graph contraction
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