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A Scenario-Based Approach to the Implementation of Refueling Stations in Drone-Based non-Emergency of Blood Supply Transportation.

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Title: A Scenario-Based Approach to the Implementation of Refueling Stations in Drone-Based non-Emergency of Blood Supply Transportation.
Authors: Saleh, Haitham1 (AUTHOR) haithamhs@kfupm.edu.sa, Sayad, Mohammed1 (AUTHOR) g201473720@kfupm.edu.sa, Alghazi, Anas1,2 (AUTHOR) alghazi@kfupm.edu.sa, Almoghathawi, Yasser1 (AUTHOR) moghathawi@kfupm.edu.sa
Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Jul2025, Vol. 50 Issue 14, p11167-11194. 28p.
Subjects: Blood groups, Blood grouping & crossmatching, Distribution planning, Traffic flow, Drone aircraft delivery
Abstract: In view of the perishable nature and complex storage requirements of certain blood products, the delivery of blood groups from blood banks to hospitals is a key aspect of the healthcare system. The centralization of blood supply facilities for economic reasons and an increase in traffic volume have led to significant delays in the use of traditional emergency vehicles. The aim of the proposed mathematical model is to minimize logistics costs by strategically positioning launch and refueling stations and assigning requests to these stations. The proposed approach employs integer binary linear programming to offer four possible scenarios that consider the flight range and supply node capacity of the drone. The study conducted a scenario-based analysis to examine the primary decision-making process for transporting blood groups and identified the optimal configuration for launching and refueling stations based on 50 group requests. The study uncovered two essential factors, NL and NR, which signify the ideal number of launching stations and the number of refueling stations situated away from the optimal launching sites. The findings offer decision-makers the precise number of stations necessary for an ideal outcome, whereas information on refueling station locations assists in resource distribution planning. Introducing refueling stations for blood supply can extend the mission range and improve coverage in nonemergency situations. Gradual implementation can prevent operational disruptions, such as station closures. This approach can also reduce delivery times and minimize delays, potentially saving lives, as refueling stations have a significant impact on the management of blood supply and logistics. [ABSTRACT FROM AUTHOR]
Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Scenario-Based Approach to the Implementation of Refueling Stations in Drone-Based non-Emergency of Blood Supply Transportation.
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  Data: <searchLink fieldCode="DE" term="%22Blood+groups%22">Blood groups</searchLink><br /><searchLink fieldCode="DE" term="%22Blood+grouping+%26+crossmatching%22">Blood grouping & crossmatching</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+planning%22">Distribution planning</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+flow%22">Traffic flow</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+aircraft+delivery%22">Drone aircraft delivery</searchLink>
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  Data: In view of the perishable nature and complex storage requirements of certain blood products, the delivery of blood groups from blood banks to hospitals is a key aspect of the healthcare system. The centralization of blood supply facilities for economic reasons and an increase in traffic volume have led to significant delays in the use of traditional emergency vehicles. The aim of the proposed mathematical model is to minimize logistics costs by strategically positioning launch and refueling stations and assigning requests to these stations. The proposed approach employs integer binary linear programming to offer four possible scenarios that consider the flight range and supply node capacity of the drone. The study conducted a scenario-based analysis to examine the primary decision-making process for transporting blood groups and identified the optimal configuration for launching and refueling stations based on 50 group requests. The study uncovered two essential factors, NL and NR, which signify the ideal number of launching stations and the number of refueling stations situated away from the optimal launching sites. The findings offer decision-makers the precise number of stations necessary for an ideal outcome, whereas information on refueling station locations assists in resource distribution planning. Introducing refueling stations for blood supply can extend the mission range and improve coverage in nonemergency situations. Gradual implementation can prevent operational disruptions, such as station closures. This approach can also reduce delivery times and minimize delays, potentially saving lives, as refueling stations have a significant impact on the management of blood supply and logistics. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s13369-024-09549-7
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        Text: English
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      – SubjectFull: Distribution planning
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      – SubjectFull: Traffic flow
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              Text: Jul2025
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