Computing Shortest Paths Amid Non-overlapping Weighted Disks

Abstract In this article, we present an approximation algorithm for solving the Weighted Region Problem amidst a set of n non-overlapping weighted disks in the plane. For a given parameter $$ \varepsilon \in (0,1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ε</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>(</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> , the length of the approximate path is at most $$ (1 +\varepsilon ) $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mi>ε</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> times larger than the length of the actual shortest path. The algorithm is based on the discretization of the space by placing points on the boundary of the disks. Using such a discretization we can use Dijkstra’s algorithm for computing a shortest path in the geometric graph obtained in (pseudo-)polynomial time.

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Journal
Results in Mathematics
Published
2025-07-19
DOI
https://doi.org/10.1007/s00025-025-02479-2
Primary Topic
Computational Geometry and Mesh Generation
Type
article
Field-Weighted Citation Impact
0.00

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article

Computing Shortest Paths Amid Non-overlapping Weighted Disks

Prosenjit Bose, Jean-Lou De Carufel, Guillermo Esteban, Anil Maheshwari
Results in Mathematics
Computational Geometry and Mesh Generation
article

Computing Shortest Paths Amid Non-overlapping Weighted Disks

Prosenjit Bose, Jean-Lou De Carufel, Guillermo Esteban, Anil Maheshwari
article en

Abstract

Abstract In this article, we present an approximation algorithm for solving the Weighted Region Problem amidst a set of n non-overlapping weighted disks in the plane. For a given parameter $$ \varepsilon \in (0,1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ε</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>(</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> , the length of the approximate path is at most $$ (1 +\varepsilon ) $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mi>ε</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> times larger than the length of the actual shortest path. The algorithm is based on the discretization of the space by placing points on the boundary of the disks. Using such a discretization we can use Dijkstra’s algorithm for computing a shortest path in the geometric graph obtained in (pseudo-)polynomial time.

Results in MathematicsVol. 80(5)
University of Ottawa (CA), Universidad de Alcalá (ES), Carleton University (CA)
Ministerio de Ciencia, Innovación y Universidades, Universidad de Alcalá, Natural Sciences and Engineering Research Council of Canada, Agencia Estatal de Investigación
Openalex Percentile: Top 65%
Computational Geometry and Mesh Generation
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