Volume 26 Issue 4
Apr.  2026
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ZHAO Jia-hong, ZHANG Jian-ping, HU Peng, ZHANG Long-fei, ZHANG Guang-yuan. Optimization model of medical UAV transportation network for biological sample leakage risk[J]. Journal of Traffic and Transportation Engineering, 2026, 26(4): 134-143. doi: 10.19818/j.cnki.1671-1637.2026.169
Citation: ZHAO Jia-hong, ZHANG Jian-ping, HU Peng, ZHANG Long-fei, ZHANG Guang-yuan. Optimization model of medical UAV transportation network for biological sample leakage risk[J]. Journal of Traffic and Transportation Engineering, 2026, 26(4): 134-143. doi: 10.19818/j.cnki.1671-1637.2026.169
shu

Optimization model of medical UAV transportation network for biological sample leakage risk

doi: 10.19818/j.cnki.1671-1637.2026.169
  • 1.

    School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, Guangdong, China

  • 2.

    Intelligent Management and Control of Low-altitude Traffic Key Laboratory of Sichuan Province, Chengdu 610041, Sichuan, China

  • 3.

    School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

  • 4.

    The Second Research Institute of CAAC, Chengdu 610041, Sichuan, China

Funds:

National Key R&D Program of China 2022YFB4300903

Key Program of the Joint Fund for Civil Aviation of National Natural Science Foundation of China U2433217

National Natural Science Foundation of China 52472332

National Natural Science Foundation of China 61803091

Sichuan Provincial Major Science and Technology Special Project-tackling Key Problems Initiative 2024ZDZX0044

National Natural Science Foundation of Guangdong Province 2025A1515010200

National Natural Science Foundation of Sichuan Province 2025ZNSFSC0394

Open Project of Intelligent Management and Control of Low-altitude Traffic Key Laboratory of Sichuan Province 2025UASKLSP01

More Information
  • Corresponding author: ZHANG Jian-ping, research fellow, PhD, E-mial: zhangjp@swjtu.edu.cn
  • Received Date: 2025-08-27
  • Accepted Date: 2026-01-23
  • Rev Recd Date: 2026-01-11
  • Publish Date: 2026-04-28
    Abstract
  • To ensure the safety of low-altitude transportation of biological samples, a multi-objective optimization model and a solution procedure are developed for the medical UAV transportation system. Considering the randomness of UAV transportation accidents, as well as the risk of biological sample leakage, a risk measurement model for medical UAV transportation is established. A medical UAV transportation network optimization model is built with the objectives of minimizing total cost and total risk. Considering the computational complexity of the proposed model, a modified NSGA-Ⅱ algorithm is adopted to design the solution procedure. Finally, a real-life case in Shenzhen, China, and several test cases are used to demonstrate the effectiveness of the proposed model and algorithm. The results show that the proposed model provides 165 effective transportation network optimization schemes for biological sample transportation in Shenzhen within 3 023.51 s. Compared with traditional risk models, the proposed risk measurement model quantitatively evaluates the transportation risk of cargo-carrying medical UAVs, and the obtained solutions reduce the total cost by an average of 18.32% and increase the degree of risk sharing by an average of 1.3 times. When solving optimization problems of different scales, the improved algorithm provides multiple non-dominated solutions within limited solution time and maintains a certain level of computational stability. The proposed model and solution algorithm provide medical UAV transportation network planning schemes and risk control methods for low-altitude transportation and emergency safety management of biological samples.

     

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