TY - JOUR
T1 - A Scenario-Based Approach to the Implementation of Refueling Stations in Drone-Based non-Emergency of Blood Supply Transportation
AU - Saleh, Haitham
AU - Sayad, Mohammed
AU - Alghazi, Anas
AU - Almoghathawi, Yasser
N1 - Publisher Copyright:
© King Fahd University of Petroleum & Minerals 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Blood group delivery
KW - Drone
KW - Launching station
KW - Logistics optimization
KW - Network design
KW - Refueling station
UR - http://www.scopus.com/inward/record.url?scp=85204379180&partnerID=8YFLogxK
U2 - 10.1007/s13369-024-09549-7
DO - 10.1007/s13369-024-09549-7
M3 - Article
AN - SCOPUS:85204379180
SN - 2193-567X
JO - Arabian Journal for Science and Engineering
JF - Arabian Journal for Science and Engineering
ER -