Original Research

Transport network modelling and optimisation for a vaccine delivery system to remote areas using unmanned aerial vehicles

Carlos Osorio-Ramírez, Catalina Moreno Castro, Jesus Gonzalez-Feliu, Antonio Comi
Journal of Transport and Supply Chain Management | Vol 19 | a1180 | DOI: https://doi.org/10.4102/jtscm.v19i0.1180 | © 2025 Carlos Osorio-Ramírez, Catalina Moreno Castro, Jesus Gonzalez-Feliu, Antonio Comi | This work is licensed under CC Attribution 4.0
Submitted: 13 April 2025 | Published: 24 November 2025

About the author(s)

Carlos Osorio-Ramírez, Faculty of Economic Sciences, Universidad Nacional de Colombia, Bogotá, Colombia
Catalina Moreno Castro, Center of Research in Innovation and Intelligence in Management, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá, Colombia
Jesus Gonzalez-Feliu, Center of Research in Innovation and Intelligence in Management, Excelia Business School, La Rochelle, France
Antonio Comi, Department of Enterprise Engineering, University of Rome Tor Vergata, Rome, Italy

Abstract

Background: Healthcare supply chains face critical challenges that increase in rural areas due to accessibility restrictions, sparce population and long distances. In Colombia, this situation is mainly reflected in rural food insecurity rates and weaknesses against illnesses. To deal with these issues, public health programmes for poor and vulnerable areas are developed, but need to be efficient and find new logistics and supply chains, taking advantage of new technologies to increase performance.
Objectives: This article proposes a vaccine delivery system using unmanned aerial vehicles (UAVs), commonly known as drones, to access remote areas. It presents a set of optimisation models for distributing vaccines to remote areas with geographical barriers.
Method: To define the vaccine delivery system, an intermodal network design model and a set of delivery options, using realistic data, are proposed.
Results: Results indicate that using an intermodal transport model where aerial transport is combined with UAVs and barges leads to a reduction of about 25% in distribution time as well as improvement in the availability of vaccines to the population in comparison to the existing system.
Conclusion: By using the proposed multimodal network design model where UAVs are used to deliver vaccines to remote areas needs can be better anticipated and healthcare supply chains be improved and supported.
Contribution: This research indicates the interest in using UAVs to access rural, inaccessible areas and its applications in the distribution of vaccines.


Keywords

healthcare transportation systems; unmanned freight transportations; transport network design; combinatorial optimisation; drones; unmanned aerial vehicles; distribution

JEL Codes

C44: Operations Research • Statistical Decision Theory; H75: State and Local Government: Health • Education • Welfare • Public Pensions; L93: Air Transportation; R41: Transportation: Demand, Supply, and Congestion • Travel Time • Safety and Accidents • Transportation Noise

Sustainable Development Goal

Goal 3: Good health and well-being

Metrics

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