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Dataset for the cumulative unmanned aerial vehicle routing problem
The Cumulative Unmanned Aerial Vehicle Routing Problem applies to area covering operations using UAVs. It is defined on a graph, the nodes of which, ensure the complete coverage of the underlying area of interest. The data generation process takes into account the characteristics of such operations,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294095/ https://www.ncbi.nlm.nih.gov/pubmed/37383775 http://dx.doi.org/10.1016/j.dib.2023.109296 |
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author | Kyriakakis, Nikolaos A. Stamadianos, Themistoklis Marinaki, Magdalene Marinakis, Yannis |
author_facet | Kyriakakis, Nikolaos A. Stamadianos, Themistoklis Marinaki, Magdalene Marinakis, Yannis |
author_sort | Kyriakakis, Nikolaos A. |
collection | PubMed |
description | The Cumulative Unmanned Aerial Vehicle Routing Problem applies to area covering operations using UAVs. It is defined on a graph, the nodes of which, ensure the complete coverage of the underlying area of interest. The data generation process takes into account the characteristics of such operations, in particular, the viewing window of the UAVs’ sensor, their maximum range, the size of the UAV fleet and the unknown locations of the targets within the area of interest. Instances are created simulating different scenarios, using different values for those UAV characteristics, as well as the different locations where the search targets might be positioned in the area of interest. |
format | Online Article Text |
id | pubmed-10294095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102940952023-06-28 Dataset for the cumulative unmanned aerial vehicle routing problem Kyriakakis, Nikolaos A. Stamadianos, Themistoklis Marinaki, Magdalene Marinakis, Yannis Data Brief Data Article The Cumulative Unmanned Aerial Vehicle Routing Problem applies to area covering operations using UAVs. It is defined on a graph, the nodes of which, ensure the complete coverage of the underlying area of interest. The data generation process takes into account the characteristics of such operations, in particular, the viewing window of the UAVs’ sensor, their maximum range, the size of the UAV fleet and the unknown locations of the targets within the area of interest. Instances are created simulating different scenarios, using different values for those UAV characteristics, as well as the different locations where the search targets might be positioned in the area of interest. Elsevier 2023-06-05 /pmc/articles/PMC10294095/ /pubmed/37383775 http://dx.doi.org/10.1016/j.dib.2023.109296 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article Kyriakakis, Nikolaos A. Stamadianos, Themistoklis Marinaki, Magdalene Marinakis, Yannis Dataset for the cumulative unmanned aerial vehicle routing problem |
title | Dataset for the cumulative unmanned aerial vehicle routing problem |
title_full | Dataset for the cumulative unmanned aerial vehicle routing problem |
title_fullStr | Dataset for the cumulative unmanned aerial vehicle routing problem |
title_full_unstemmed | Dataset for the cumulative unmanned aerial vehicle routing problem |
title_short | Dataset for the cumulative unmanned aerial vehicle routing problem |
title_sort | dataset for the cumulative unmanned aerial vehicle routing problem |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294095/ https://www.ncbi.nlm.nih.gov/pubmed/37383775 http://dx.doi.org/10.1016/j.dib.2023.109296 |
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