Research on Reconfiguration of Medical Waste Recovery Logistics Network in the Bordering Areas of Shanghai and Jiangsu

Abstract

With the rapid development of the healthcare industry in China, the safe and efficient disposal of medical waste (MW) has become a critical issue in environmental governance and public health safety. The traditional territory-based MW disposal model has caused severe resource mismatch between the bordering areas of Shanghai and Jiangsu, where geographical proximity coexists with fragmented administrative governance. To solve this contradiction, this study converts the intangible administrative barrier into measurable administrative coordination cost, and establishes a bi-objective optimization model with the core objectives of minimizing total comprehensive cost and minimizing total carbon emissions. Aiming at the limitation of traditional K-means algorithm that only relies on geographic distance, an improved K-means clustering algorithm integrated with administrative cost and carbon cost weights is designed, and combined with an improved Genetic Algorithm (GA) to complete model solving. Taking Chongming District of Shanghai and Qidong City of Jiangsu as the empirical case, this study conducts a quantitative analysis with 218 medical institutions as research samples. The results show that compared with the traditional independent disposal model within administrative regions, the optimized cross-regional collaborative scheme reduces the total transportation mileage by 18.04%, the total operation cost by 13.20%, and the total carbon emissions by 17.65%, while increasing the 48-hour collection and transportation compliance rate from 92.5% to 99.8%. This study provides a scientific decision-making reference for cross-regional MW governance in the Yangtze River Delta, and offers a replicable theoretical framework for breaking administrative barriers and promoting the low-carbon transformation of reverse logistics networks.