Abstract

Urban Air Mobility (UAM) involves the use of both piloted and autonomous aerial vehicles, ranging from small unmanned aerial vehicles (UAVs), such as drones, to larger passenger-carrying personal air vehicles (PAVs). This ground-breaking approach holds the potential to transform healthcare logistics by facilitating the fast and efficient transportation of organs between hospitals, addressing critical mobility challenges in healthcare delivery. However, scheduling organ transport is fraught with challenges, including (1) the limited availability of UAM vehicles at specific hospital branches, (2) the critical Cold Ischemia Time (CIT) for various organs, and (3) the high flying costs associated with moving organs from source to destination. This paper proposes a heuristic solution that simultaneously tackles these challenges and provides an approximate solution in polynomial time. To evaluate the performance of our algorithm, we compare it against a baseline, which prioritizes cost efficiency. Experimental evaluation of CITRUS demonstrates notable performance improvements over the baseline, with an average increase of 3% in delivery success rates.

Department(s)

Computer Science

Comments

National Science Foundation, Grant ECCS-2319995

Keywords and Phrases

cost optimization; healthcare; organ transport; path optimization; route-planning; Urban air mobility; vertical take-off and landing vehicles

International Standard Serial Number (ISSN)

2766-8576; 2836-5348

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 2025

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