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Discrete mission planning algorithm for air-sea integrated search model
The selection of optimal search effort for air-sea integrated search has become the most concerned issue for maritime search and rescue (MSAR) departments. Helicopters play an important role in maritime search because of their strong maneuverability and hovering ability. In this work, the requiremen...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379196/ https://www.ncbi.nlm.nih.gov/pubmed/34417483 http://dx.doi.org/10.1038/s41598-021-95477-7 |
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author | Yu, Yixiong |
author_facet | Yu, Yixiong |
author_sort | Yu, Yixiong |
collection | PubMed |
description | The selection of optimal search effort for air-sea integrated search has become the most concerned issue for maritime search and rescue (MSAR) departments. Helicopters play an important role in maritime search because of their strong maneuverability and hovering ability. In this work, the requirements of maritime search were analyzed, from which a global optimization model with quantitative constraints for vessels and aircraft was developed by setting the least search time as single-objective optimization problem; then the improved Dinkelbach algorithm was used to solve the continuous programming problem, and the discrete mission planning algorithm was used to improve the calculation accuracy of search time and area. A case study shows that the errors in calculating search time and area decrease from 12–18 min to 36 s and from 76.5 to 0.45 n mile(2), respectively. The results obtained from the discrete mission planning algorithm can provide better guidance for MASR departments in selecting optimal search scheme. |
format | Online Article Text |
id | pubmed-8379196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-83791962021-08-27 Discrete mission planning algorithm for air-sea integrated search model Yu, Yixiong Sci Rep Article The selection of optimal search effort for air-sea integrated search has become the most concerned issue for maritime search and rescue (MSAR) departments. Helicopters play an important role in maritime search because of their strong maneuverability and hovering ability. In this work, the requirements of maritime search were analyzed, from which a global optimization model with quantitative constraints for vessels and aircraft was developed by setting the least search time as single-objective optimization problem; then the improved Dinkelbach algorithm was used to solve the continuous programming problem, and the discrete mission planning algorithm was used to improve the calculation accuracy of search time and area. A case study shows that the errors in calculating search time and area decrease from 12–18 min to 36 s and from 76.5 to 0.45 n mile(2), respectively. The results obtained from the discrete mission planning algorithm can provide better guidance for MASR departments in selecting optimal search scheme. Nature Publishing Group UK 2021-08-20 /pmc/articles/PMC8379196/ /pubmed/34417483 http://dx.doi.org/10.1038/s41598-021-95477-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yu, Yixiong Discrete mission planning algorithm for air-sea integrated search model |
title | Discrete mission planning algorithm for air-sea integrated search model |
title_full | Discrete mission planning algorithm for air-sea integrated search model |
title_fullStr | Discrete mission planning algorithm for air-sea integrated search model |
title_full_unstemmed | Discrete mission planning algorithm for air-sea integrated search model |
title_short | Discrete mission planning algorithm for air-sea integrated search model |
title_sort | discrete mission planning algorithm for air-sea integrated search model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379196/ https://www.ncbi.nlm.nih.gov/pubmed/34417483 http://dx.doi.org/10.1038/s41598-021-95477-7 |
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