On approximating shortest paths in weighted triangular tessellations Article Swipe
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· 2023
· Open Access
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· DOI: https://doi.org/10.1016/j.artint.2023.103898
We study the quality of weighted shortest paths when a continuous 2-dimensional space is discretized by a weighted triangular tessellation. In order to evaluate how well the tessellation approximates the 2-dimensional space, we study three types of shortest paths: a weighted shortest path $ \mathit{SP_w}(s,t) $, which is a shortest path from $ s $ to $ t $ in the space; a weighted shortest vertex path $ \mathit{SVP_w}(s,t) $, which is an any-angle shortest path; and a weighted shortest grid path $ \mathit{SGP_w}(s,t) $, which is a shortest path whose edges are edges of the tessellation. Given any arbitrary weight assignment to the faces of a triangular tessellation, thus extending recent results by Bailey et al. [Path-length analysis for grid-based path planning. Artificial Intelligence, 301:103560, 2021], we prove upper and lower bounds on the ratios $ \frac{\lVert \mathit{SGP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} $, $ \frac{\lVert \mathit{SVP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} $, $ \frac{\lVert \mathit{SGP_w}(s,t)\rVert}{\lVert \mathit{SVP_w}(s,t)\rVert} $, which provide estimates on the quality of the approximation. It turns out, surprisingly, that our worst-case bounds are independent of any weight assignment. Our main result is that $ \frac{\lVert \mathit{SGP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} = \frac{2}{\sqrt{3}} \approx 1.15 $ in the worst case, and this is tight. As a corollary, for the weighted any-angle path $ \mathit{SVP_w}(s,t) $ we obtain the approximation result $ \frac{\lVert \mathit{SVP_w}(s,t)\rVert}{\lVert \mathit{SP_w}(s,t)\rVert} \lessapprox 1.15 $.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.artint.2023.103898
- OA Status
- hybrid
- References
- 40
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- OpenAlex ID
- https://openalex.org/W4226303121
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https://openalex.org/W4226303121Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.artint.2023.103898Digital Object Identifier
- Title
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On approximating shortest paths in weighted triangular tessellationsWork title
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preprintOpenAlex work type
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enPrimary language
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2023Year of publication
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2023-03-05Full publication date if available
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Prosenjit Bose, Guillermo Esteban, David Orden, Rodrigo I. SilveiraList of authors in order
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https://doi.org/10.1016/j.artint.2023.103898Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.artint.2023.103898Direct OA link when available
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Combinatorics, Shortest path problem, Vertex (graph theory), Tessellation (computer graphics), Path (computing), Mathematics, Hexagonal tiling, Space (punctuation), Discrete mathematics, Computer science, Grid, Geometry, Operating system, Programming language, GraphTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.shortest | 6, 37, 41, 49, 64, 74, 79, 88 |
| abstract_inverted_index.weighted | 5, 17, 40, 63, 78, 201 |
| abstract_inverted_index.any-angle | 73, 202 |
| abstract_inverted_index.arbitrary | 99 |
| abstract_inverted_index.estimates | 153 |
| abstract_inverted_index.extending | 110 |
| abstract_inverted_index.planning. | 122 |
| abstract_inverted_index.Artificial | 123 |
| abstract_inverted_index.assignment | 101 |
| abstract_inverted_index.continuous | 10 |
| abstract_inverted_index.corollary, | 198 |
| abstract_inverted_index.grid-based | 120 |
| abstract_inverted_index.triangular | 18, 107 |
| abstract_inverted_index.worst-case | 166 |
| abstract_inverted_index.301:103560, | 125 |
| abstract_inverted_index.\lessapprox | 216 |
| abstract_inverted_index.assignment. | 173 |
| abstract_inverted_index.discretized | 14 |
| abstract_inverted_index.independent | 169 |
| abstract_inverted_index.[Path-length | 117 |
| abstract_inverted_index.\frac{\lVert | 137, 142, 147, 180, 213 |
| abstract_inverted_index.approximates | 28 |
| abstract_inverted_index.tessellation | 27 |
| abstract_inverted_index.2-dimensional | 11, 30 |
| abstract_inverted_index.Intelligence, | 124 |
| abstract_inverted_index.approximation | 210 |
| abstract_inverted_index.surprisingly, | 163 |
| abstract_inverted_index.tessellation, | 108 |
| abstract_inverted_index.tessellation. | 19, 96 |
| abstract_inverted_index.approximation. | 159 |
| abstract_inverted_index.\frac{2}{\sqrt{3}} | 184 |
| abstract_inverted_index.\mathit{SP_w}(s,t) | 44 |
| abstract_inverted_index.\mathit{SGP_w}(s,t) | 83 |
| abstract_inverted_index.\mathit{SVP_w}(s,t) | 68, 205 |
| abstract_inverted_index.\mathit{SP_w}(s,t)\rVert} | 139, 144, 182, 215 |
| abstract_inverted_index.\mathit{SVP_w}(s,t)\rVert} | 149 |
| abstract_inverted_index.\mathit{SGP_w}(s,t)\rVert}{\lVert | 138, 148, 181 |
| abstract_inverted_index.\mathit{SVP_w}(s,t)\rVert}{\lVert | 143, 214 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.00936648 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |