Collaborative Reverse Logistics Network for Infectious Medical Waste Management during the COVID-19 Outbreak
Xuan Luo and
Wenzhu Liao ()
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Xuan Luo: School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China
Wenzhu Liao: School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China
IJERPH, 2022, vol. 19, issue 15, 1-28
Abstract:
The development of COVID-19 in China has gradually become normalized; thus, the prevention and control of the pandemic has encountered new problems: the amount of infectious medical waste (IMW) has increased sharply; the location of outbreaks are highly unpredictable; and the pandemic occurs everywhere. Thus, it is vital to design an effective IMW reverse logistics network to cope with these problems. This paper firstly introduces mobile processing centers (MPCs) into an IMW reverse logistics network for resource-saving, quick response, and the sufficient capacity of processing centers. Then, a multi-participant-based (public central hospitals, disposal institutions, the logistics providers, and the government) collaborative location and a routing optimization model for IMW reverse logistics are built from an economic, environmental perspective. An augmented ε-constraint method is developed to solve this proposed model. Through a case study in Chongqing, it is found that for uncertain outbreak situations, fixed processing centers (FPCs) and MPCs can form better disposal strategies. MPC can expand the processing capacity flexibly in response to the sudden increase in IMW. The results demonstrate good performance in reduction in cost and infection risk, which could greatly support the decision making of IMW management for the government in the pandemic prevention and control.
Keywords: infectious medical waste; reverse logistics; collaborative; multi-participant; optimization (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)
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