Location planning techniques for Internet provider service unmanned aerial vehicles during crisis
In situations where conventional communication networks are compromised, deploying Internet Provider Service Unmanned Aerial Vehicles (UAVs) becomes essential for re-establishing connectivity. This study presents a hyperheuristic framework aimed at optimizing the positioning and management of these...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024020760 |
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| author | Kassem Danach Hassan Harb Ameer Sardar Kwekha Rashid Mutaz A.B. Al-Tarawneh Wael Hosny Fouad Aly |
| author_facet | Kassem Danach Hassan Harb Ameer Sardar Kwekha Rashid Mutaz A.B. Al-Tarawneh Wael Hosny Fouad Aly |
| author_sort | Kassem Danach |
| collection | DOAJ |
| description | In situations where conventional communication networks are compromised, deploying Internet Provider Service Unmanned Aerial Vehicles (UAVs) becomes essential for re-establishing connectivity. This study presents a hyperheuristic framework aimed at optimizing the positioning and management of these UAVs, with a focus on enhancing coverage, reducing latency, and managing operational costs. The framework employs a dynamic selection of multiple low-level heuristics, guided by real-time problem conditions and a Monte Carlo-based decision process. The performance of this approach was evaluated through simulations across 40 different scenarios, encompassing urban, suburban, rural, and mixed environments. The results show that the hyperheuristic method consistently delivered high coverage, achieving 94.6% in urban settings, 88.3% in suburban areas, 82.0% in rural regions, and 85.0% in mixed conditions. These outcomes highlight the flexibility and effectiveness of the hyperheuristic approach in adapting to various crisis scenarios. This research not only provides practical insights for UAV deployment but also advances the field of combinatorial optimization through innovative hyperheuristic techniques. |
| format | Article |
| id | doaj-art-de847dd7627049acbdbc435a54381c50 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-de847dd7627049acbdbc435a54381c502025-01-09T06:14:29ZengElsevierResults in Engineering2590-12302025-03-0125103833Location planning techniques for Internet provider service unmanned aerial vehicles during crisisKassem Danach0Hassan Harb1Ameer Sardar Kwekha Rashid2Mutaz A.B. Al-Tarawneh3Wael Hosny Fouad Aly4Basic and Applied Sciences Research Center, Al Maaref University, Beirut, LebanonCollege of Engineering and Technology, American University of the Middle East, Kuwait; Corresponding author.Artificial Intelligence, Universiti Teknologi Malaysia-UTM, Malaysia; University of Sulaimani, Sulaymaniyah, IraqCollege of Engineering and Technology, American University of the Middle East, KuwaitCollege of Engineering and Technology, American University of the Middle East, KuwaitIn situations where conventional communication networks are compromised, deploying Internet Provider Service Unmanned Aerial Vehicles (UAVs) becomes essential for re-establishing connectivity. This study presents a hyperheuristic framework aimed at optimizing the positioning and management of these UAVs, with a focus on enhancing coverage, reducing latency, and managing operational costs. The framework employs a dynamic selection of multiple low-level heuristics, guided by real-time problem conditions and a Monte Carlo-based decision process. The performance of this approach was evaluated through simulations across 40 different scenarios, encompassing urban, suburban, rural, and mixed environments. The results show that the hyperheuristic method consistently delivered high coverage, achieving 94.6% in urban settings, 88.3% in suburban areas, 82.0% in rural regions, and 85.0% in mixed conditions. These outcomes highlight the flexibility and effectiveness of the hyperheuristic approach in adapting to various crisis scenarios. This research not only provides practical insights for UAV deployment but also advances the field of combinatorial optimization through innovative hyperheuristic techniques.http://www.sciencedirect.com/science/article/pii/S2590123024020760Unmanned aerial vehiclesScheduling problemHyperheuristicMetaheuristicCrisis management |
| spellingShingle | Kassem Danach Hassan Harb Ameer Sardar Kwekha Rashid Mutaz A.B. Al-Tarawneh Wael Hosny Fouad Aly Location planning techniques for Internet provider service unmanned aerial vehicles during crisis Results in Engineering Unmanned aerial vehicles Scheduling problem Hyperheuristic Metaheuristic Crisis management |
| title | Location planning techniques for Internet provider service unmanned aerial vehicles during crisis |
| title_full | Location planning techniques for Internet provider service unmanned aerial vehicles during crisis |
| title_fullStr | Location planning techniques for Internet provider service unmanned aerial vehicles during crisis |
| title_full_unstemmed | Location planning techniques for Internet provider service unmanned aerial vehicles during crisis |
| title_short | Location planning techniques for Internet provider service unmanned aerial vehicles during crisis |
| title_sort | location planning techniques for internet provider service unmanned aerial vehicles during crisis |
| topic | Unmanned aerial vehicles Scheduling problem Hyperheuristic Metaheuristic Crisis management |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024020760 |
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