ERI: Realistic Drone Integration in Rural Healthcare Supply Chains

This Engineering Research Initiation (ERI) award supports research enabling the integration of drone technology into healthcare logistics to address the challenges of access to medical supplies in rural areas. Rural communities are hindered by limited infrastructure, vast distances, rugged terrain and severe weather conditions, which significantly impact the timely and efficient delivery of essential healthcare supplies. Despite the recognized potential of drones to enhance healthcare delivery in such settings, optimizing drone operations considering practical constraints such as environmental factors (e.g., weather and wind conditions) and their impact on operational performance (e.g., range and payload) has proven challenging. This award addresses this need by developing and analyzing mathematical models to support drone integration into multi-modal transportation networks, considering the uncertainties of weather conditions and the specific needs of each delivery. This initiative aims not only to enhance healthcare access in rural areas but also to advance the state of the art in healthcare logistics, contribute to educational and diversity efforts in STEM, and ultimately support the national health and prosperity by ensuring efficient and equitable healthcare access across all communities. This research will develop a decision-support tool for improving rural healthcare logistics through strategic drone use given variable weather and operational conditions. Probabilistic energy consumption modeling will allow the incorporation of uncertainties in drone performance into a robust optimization model that designs the logistic network under worst-case scenarios while also optimizing reliable operations to facilitate collaboration among multiple transportation modes, including drones. Innovative solution algorithms will be developed to handle complexities due to time-sensitive demand, and simulation experiments will be conducted to verify and validate the effectiveness of the drone-based delivery system. The simulation will be designed using both synthetic data that mimics rural landscapes and real-world data related to pandemic supply chains. Numerical experiments will evaluate the system's overall effectiveness by comparing scenarios with and without drone use, examining the trade-offs between operational efficiency and equitable distribution of medical supplies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.