School of Economics and Management, China University of Geosciences, Wuhan 430074, China.
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.
Int J Environ Res Public Health. 2020 Aug 12;17(16):5831. doi: 10.3390/ijerph17165831.
In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony-tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China-considered the first city to suffer from COVID-19-was chosen as an example of verification; the two-level model and the immune algorithm-ant colony optimization-tabu search (IA-ACO-TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.
针对 COVID-19 这一突发公共卫生事件，医院到处理站的医疗废物运输效率是一个值得研究的问题。本文基于 COVID-19 的实际情况和环境影响评估指南，利用免疫算法建立了城市医疗废物储存点的选址模型。针对临时储存站的选择和现实的运输需求，利用蚁群禁忌混合算法建立了医院与临时储存站之间医疗废物的运输效率模型。为了明确这种情况，选择中国湖北省武汉市作为首例 COVID-19 城市作为验证实例；采用两级模型和免疫算法-蚁群优化-禁忌搜索（IA-ACO-TS）算法进行模拟和测试，取得了良好的验证效果。在一定程度上，提出了基于中转临时储存站的医疗废物处理问题的模型和算法，我们相信这对中国和其他国家应对此类突发公共卫生事件调配医疗废物具有深远的意义。
