CGDSMay 8

Touring a Sequence of Orthogonal Polygons

arXiv:2605.0788290.5
AI Analysis

This work provides the first subquadratic algorithms for this problem in the orthogonal setting, improving upon previous Õ(nk) and Õ(nk^2) algorithms for convex polygons under L2 distance.

The paper studies the problem of computing a shortest tour visiting a sequence of orthogonal polygons under Manhattan distance, achieving a truly subquadratic Õ(n^{2-1/48}) algorithm for disjoint consecutive polygons, and Õ(n) for ortho-convex polygons, among other results.

We study the problem of computing a shortest tour that visits a sequence of $k$ polygons $P_1,\dots, P_k$ with a total number of $n$ vertices. A tour is an oriented curve such that there exist points $p_i\in P_i$ for all $i$ where $p_i$ appears not after $p_{i+1}$. In a seminal paper Dror, Efrat, Lubiw, and Mitchell (STOC 2003) considered the problem under $L_2$ distance, and gave $\widetilde O(nk)$ and $\widetilde O(nk^2)$ algorithms for disjoint and intersecting convex polygons, respectively. This paper considers the orthogonal setting, where the input polygons have axis-aligned edges and the distance metric is the Manhattan distance. We obtain the following results: - as our main contribution, a truly subquadratic $\widetilde O(n^{2-\frac{1}{48}})$ algorithm when consecutive polygons in the sequence are disjoint; - an $\widetilde O(n)$ algorithm for ortho-convex polygons when consecutive polygons are disjoint; - an $O(n)$ algorithm for axis-aligned rectangles; - $\widetilde O(n^2)$ and $\widetilde O(n^{1.5}k^2)$ algorithms without restrictions. Our algorithms build on a wide range of techniques, including additively weighted Voronoi diagrams, rectangle decompositions, persistent data structures, and dynamic distance oracles for weighted planar graphs.

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