Charging Station Distribution Optimization Using Drone Fleet in a Disaster
A disaster is an unforeseen calamity that can cause damage to properties and can bring about a loss of human lives. Usually, many relief supplies, such as clean water, food, and medical supplies, are required by disaster victims. Quick response and rapid distribution of essential relief items into t...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/7329346 |
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| author | Zohaib Hassan Syed Irtiza Ali Shah Ahsan Sarwar Rana |
| author_facet | Zohaib Hassan Syed Irtiza Ali Shah Ahsan Sarwar Rana |
| author_sort | Zohaib Hassan |
| collection | DOAJ |
| description | A disaster is an unforeseen calamity that can cause damage to properties and can bring about a loss of human lives. Usually, many relief supplies, such as clean water, food, and medical supplies, are required by disaster victims. Quick response and rapid distribution of essential relief items into the affected region can save countless lives and prevent or slow down the effects of disasters. In this regard, disaster management comes into play, which is highly dependent on the topography and access of the disaster-hit area. If the disaster-hit site has little or no road connectivity, the use of UAVs/drones becomes essential in delivering health packages to the affected areas to assist with humanitarian aid. Since the battery capacity of the drone is limited, UAVs/drones require charging stations located at various places to carry out the necessary relief work. These charging stations should be transported using road infrastructure and preinstalled in disaster-prone areas, as access to these areas may be denied once the disaster hits. This article presents a novel optimization model to distribute relief items to disaster-hit areas. The objective of this model is to optimize the location and the number of the charging stations. We consider the relative priority of locations where a preference is given to locations with higher priority levels. The optimal number of charging stations and optimal routes has also been determined by using our optimization model. To illustrate the use of our model, numerical examples have been simulated for a different number of targets. Through our numerical simulation, it was observed that the drone’s maximum distance capacity is the key factor in determining the optimal grid size, which directly correlates to the number of charging stations. |
| format | Article |
| id | doaj-art-06bf2f3c46a6475da278cb894499718b |
| institution | Kabale University |
| issn | 1687-9619 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-06bf2f3c46a6475da278cb894499718b2025-02-03T05:50:44ZengWileyJournal of Robotics1687-96192022-01-01202210.1155/2022/7329346Charging Station Distribution Optimization Using Drone Fleet in a DisasterZohaib Hassan0Syed Irtiza Ali Shah1Ahsan Sarwar Rana2Electrical and Computer Engineering DepartmentInstitute of Aerospace and Aeronautical EngineeringElectrical and Computer Engineering DepartmentA disaster is an unforeseen calamity that can cause damage to properties and can bring about a loss of human lives. Usually, many relief supplies, such as clean water, food, and medical supplies, are required by disaster victims. Quick response and rapid distribution of essential relief items into the affected region can save countless lives and prevent or slow down the effects of disasters. In this regard, disaster management comes into play, which is highly dependent on the topography and access of the disaster-hit area. If the disaster-hit site has little or no road connectivity, the use of UAVs/drones becomes essential in delivering health packages to the affected areas to assist with humanitarian aid. Since the battery capacity of the drone is limited, UAVs/drones require charging stations located at various places to carry out the necessary relief work. These charging stations should be transported using road infrastructure and preinstalled in disaster-prone areas, as access to these areas may be denied once the disaster hits. This article presents a novel optimization model to distribute relief items to disaster-hit areas. The objective of this model is to optimize the location and the number of the charging stations. We consider the relative priority of locations where a preference is given to locations with higher priority levels. The optimal number of charging stations and optimal routes has also been determined by using our optimization model. To illustrate the use of our model, numerical examples have been simulated for a different number of targets. Through our numerical simulation, it was observed that the drone’s maximum distance capacity is the key factor in determining the optimal grid size, which directly correlates to the number of charging stations.http://dx.doi.org/10.1155/2022/7329346 |
| spellingShingle | Zohaib Hassan Syed Irtiza Ali Shah Ahsan Sarwar Rana Charging Station Distribution Optimization Using Drone Fleet in a Disaster Journal of Robotics |
| title | Charging Station Distribution Optimization Using Drone Fleet in a Disaster |
| title_full | Charging Station Distribution Optimization Using Drone Fleet in a Disaster |
| title_fullStr | Charging Station Distribution Optimization Using Drone Fleet in a Disaster |
| title_full_unstemmed | Charging Station Distribution Optimization Using Drone Fleet in a Disaster |
| title_short | Charging Station Distribution Optimization Using Drone Fleet in a Disaster |
| title_sort | charging station distribution optimization using drone fleet in a disaster |
| url | http://dx.doi.org/10.1155/2022/7329346 |
| work_keys_str_mv | AT zohaibhassan chargingstationdistributionoptimizationusingdronefleetinadisaster AT syedirtizaalishah chargingstationdistributionoptimizationusingdronefleetinadisaster AT ahsansarwarrana chargingstationdistributionoptimizationusingdronefleetinadisaster |