Boosting Rectilinear Steiner Minimum Tree Algorithms with Augmented Bounding Volume Hierarchy

Fuente: arXiv
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Main Authors: Yang, Puhan, Li, Guchan
Format: Preprint
Published: 2025
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author Yang, Puhan
Li, Guchan
author_facet Yang, Puhan
Li, Guchan
contents The rectilinear Steiner minimum tree (RSMT) problem computes the shortest network connecting a given set of points using only horizontal and vertical lines, possibly adding extra points (Steiner points) to minimize the total length. RSMT solvers seek to balance speed and accuracy. In this work, we design a framework to boost existing RSMT solvers, extending the Pareto front. Combined with GeoSteiner, our algorithm reaches 5.16\% length error on nets with 1000 pins. The average time needed is 0.46 seconds. This provides an effective way to solve large-scale RSMT problems with small-scale solvers.
format Preprint
id arxiv_https___arxiv_org_abs_2503_02319
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Boosting Rectilinear Steiner Minimum Tree Algorithms with Augmented Bounding Volume Hierarchy
Yang, Puhan
Li, Guchan
Data Structures and Algorithms
Computational Geometry
Discrete Mathematics
The rectilinear Steiner minimum tree (RSMT) problem computes the shortest network connecting a given set of points using only horizontal and vertical lines, possibly adding extra points (Steiner points) to minimize the total length. RSMT solvers seek to balance speed and accuracy. In this work, we design a framework to boost existing RSMT solvers, extending the Pareto front. Combined with GeoSteiner, our algorithm reaches 5.16\% length error on nets with 1000 pins. The average time needed is 0.46 seconds. This provides an effective way to solve large-scale RSMT problems with small-scale solvers.
title Boosting Rectilinear Steiner Minimum Tree Algorithms with Augmented Bounding Volume Hierarchy
topic Data Structures and Algorithms
Computational Geometry
Discrete Mathematics
url https://arxiv.org/abs/2503.02319