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Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation

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  • Tingxi Wen
  • Zhongnan Zhang
  • Kelvin K L Wong

Abstract

Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood’s temperature model during transportation, the UAVs’ scheduling and routes’ planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood’s temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

Suggested Citation

  • Tingxi Wen & Zhongnan Zhang & Kelvin K L Wong, 2016. "Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-22, May.
    • Handle: RePEc:plo:pone00:0155176
    DOI: 10.1371/journal.pone.0155176
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    References listed on IDEAS

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    Cited by:

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    2. Yan, Rui & Zhu, Xiaoping & Zhu, Xiaoning & Peng, Rui, 2022. "Optimal routes and aborting strategies of trucks and drones under random attacks," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Marlena Robakowska & Daniel Ślęzak & Przemysław Żuratyński & Anna Tyrańska-Fobke & Piotr Robakowski & Paweł Prędkiewicz & Katarzyna Zorena, 2022. "Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies," IJERPH, MDPI, vol. 19(17), pages 1-15, August.
    4. Asadpour, Milad & Olsen, Tava Lennon & Boyer, Omid, 2022. "An updated review on blood supply chain quantitative models: A disaster perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    5. Nyaaba, Albert Apotele & Ayamga, Matthew, 2021. "Intricacies of medical drones in healthcare delivery: Implications for Africa," Technology in Society, Elsevier, vol. 66(C).
    6. Fidel Aznar & Mar Pujol & Ramón Rizo & Carlos Rizo, 2018. "Modelling multi-rotor UAVs swarm deployment using virtual pheromones," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-20, January.

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