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Reverse Logistics Network Design for Medical Waste Disposal under the Scenario of Uncertain Proposal Demand

Author

Listed:
  • Lan Zhu

    (School of Modern Post, Xi’an University of Posts and Telecommunications, Xi’an 710061, China)

  • Tao Ding

    (School of Modern Post, Xi’an University of Posts and Telecommunications, Xi’an 710061, China)

  • Zhuofan Liu

    (School of Modern Post, Xi’an University of Posts and Telecommunications, Xi’an 710061, China)

Abstract

With the development of the healthcare industry, the demand for medical services and protective equipment is boosted, causing the generation rate of infectious medical waste to increase rapidly. Therefore, it is of utmost importance for decision makers to effectively predict the potential risks and propose corresponding solutions. This paper investigates the reverse logistics network optimization for medical waste under the conditions of an uncertain proposal demand. Firstly, a prediction model of medical waste based on the SEIR epidemiological dynamics is constructed, in which both routine and public health emergency scenarios are simultaneously considered. Secondly, a bi-objective location-routing optimization model for a medical waste reverse logistics network is proposed, by simultaneously optimizing the total economic cost and potential risk throughout the entire logistics process. Subsequently, an NSGA-II algorithm is designed for a model solution in response to the model’s characteristics. The epidemiological dynamics-based prediction model is validated by the real case to be scientifically effective in predicting the amount of generated medical waste with a mean absolute percentage error (MAPE) of 18.08%. The constructed reverse logistics network model and the NSGA II algorithm provide a medical waste process center location, transportation routing, and vehicle selection solutions for both routine and emergency public health cases of Xi’an city with large, medium, and small scales. The above results indicate that the research scheme proposed in this paper could significantly reduce the medical waste logistics-related risks and costs and provide decision makers with more safe and reliable logistical solutions.

Suggested Citation

  • Lan Zhu & Tao Ding & Zhuofan Liu, 2024. "Reverse Logistics Network Design for Medical Waste Disposal under the Scenario of Uncertain Proposal Demand," Sustainability, MDPI, vol. 16(7), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2996-:d:1369813
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    References listed on IDEAS

    as
    1. Ming Liu & Yihong Xiao, 2015. "Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-12, March.
    2. Wang, Sophie Xuefei & Fu, Yu Benjamin & Zhang, Zhe George, 2015. "Population growth and the environmental Kuznets curve," China Economic Review, Elsevier, vol. 36(C), pages 146-165.
    3. Xuan Luo & Wenzhu Liao, 2022. "Collaborative Reverse Logistics Network for Infectious Medical Waste Management during the COVID-19 Outbreak," IJERPH, MDPI, vol. 19(15), pages 1-28, August.
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