Single-Source Shortest Paths and Almost Exact Diameter in Pseudodisk Graphs

2026-04-25

AI Summary

This work addresses the lack of efficient algorithms for single-source shortest paths (SSSP) and graph diameter computation in intersection graphs of planar geometric objects with constant complexity, such as pseudodisks. The authors propose a randomized approach based on union complexity and introduce a star-shaped $r$-clustering structure. They present the first nearly linear-time SSSP algorithm for general pseudodisk intersection graphs, running in $O(n \cdot 2^{\alpha(n)} \cdot \log^2 n)$ time. Additionally, they design a diameter approximation algorithm with additive error 2 and running time $\tilde{O}(n^{2 - 1/14})$, improving upon the previous $\tilde{O}(n^{2 - 1/18})$ bound, and construct a distance oracle supporting $O(1)$-time queries.

Technology Category

• Search and Optimization: Combinatorial Optimization
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semantics
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

We study SINGLE-SOURCE SHORTEST PATH (SSSP) on unweighted intersection graphs whose node set corresponds to a set of $n$ constant-complexity objects in the plane. We prove SSSP can be solved in $O(U(n)\ \mathrm{polylog}\,n)$ expected time for any class of objects whose union complexity is $U(n)$. In particular, we obtain an $O(n 2^{α(n)}\log^2 n)$ algorithm for arbitrary pseudodisks, and an $O(λ_{s+2}(n)2^{O(\log^* n)} \log^2 n)$ algorithm for locally fat objects. This significantly extends the class of objects for which SSSP can be solved in $O(n\ \mathrm{polylog}\, n)$ time: so far, $O(n\ \mathrm{polylog}\, n)$ SSSP algorithms were not even known for pseudodisks that are fat and convex and similarly-sized. Our second result concerns the DIAMETER problem, which asks for the maximum distance between any two nodes in a graph. Even for intersection graphs, near-quadratic algorithms are difficult to obtain, and the $O(n^2\ \mathrm{polylog}\, n)$ running time that follows from our SSSP algorithm is the first near-quadratic running time for such general classes of intersection graphs. Obtaining subquadratic running time is even more challenging. We prove that the diameter of a set of arbitrary pseudodisks can be computed almost exactly, namely up to an additive error of 2, in $\tilde{O}(n^{2-1/14})$ expected time. This generalizes and speeds up a recent algorithm by Chang, Gao, and Le~(SoCG 2024) that works for similarly-sized disks (or similarly-sized pseudodisks that are fat and satisfy a strong monotonicity assumption) and runs in $\tilde{O}(n^{2-1/18})$ time. To this end, we develop a so-called star-based $r$-clustering for intersection graphs of pseudodisks, which is interesting in its own right. Our star-based $r$-clustering can also be used to obtain an almost exact distance oracle for pseudodisks that uses $O(n^{2-1/13})$ storage and has $O(1)$ query time.

Problem

• Single-Source Shortest Paths
• Diameter
• Pseudodisk Graphs
• Intersection Graphs
• Almost Exact Algorithm

Innovation

• pseudodisk graphs
• single-source shortest paths
• almost exact diameter
• star-based r-clustering
• intersection graphs