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  • Journal of Transportation and Logistics
  • Cilt: 10 Sayı: 2
  • Unmanned Aerial Vehicle Routing and Facility Location Selection for Healthcare Supply Chain Manageme...

Unmanned Aerial Vehicle Routing and Facility Location Selection for Healthcare Supply Chain Management: A Case Study in Türkiye

Authors : Mevlut Evci, Celal Burak Özçelik, Tarik Ataman, Yıldız Köse
Pages : 327-343
Doi:10.26650/JTL.2025.1607328
View : 123 | Download : 375
Publication Date : 2025-11-11
Article Type : Research Paper
Abstract :Healthcare supply chain management is of great importance, particularly for hospitals. To manage medical supply chains quickly and effectively requires new and optimized logistics strategies. The use of an unmanned aerial vehicle (UAV) enables the swift delivery of medical supplies, overcoming obstacles like traffic, natural disasters, or infrastructure damage, and saving lives in critical situations. This study focuses on the distribution phase of emergency medical supply chains using electric UAVs, aiming to save lives during crises by establishing an efficient, technological, and sustainable transportation system in healthcare. The strategic locations of the charging stations, which can also serve as medical supply depots, and the optimal routes for the vehicles are integrated. Using Multi-Criteria Decision-Making (MCDM) techniques, specifically the AHP and TOPSIS methods, the optimal charging points for electric unmanned aerial vehicles are determined by considering various criteria. From these identified facilities, a multi-depot vehicle routing model was developed for supplying emergency medical supplies to hospitals, considering vehicle characteristics, hospital demand quantities, and facility capacities. This integrated methodology was applied to the province of Trabzon in Türkiye. Three different routes covering a total distance of 29.59 kilometres were generated to supply medical materials from five identified facilities to ten hospitals.
Keywords : Medical supply chain management, Vehicle Routing Problem, AHP, TOPSIS

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