基于聚类-重心法的应急物流配送中心选址

Location selection of emergency logistics distribution center based on clustering-center of gravity method

为确保应急物流配送中心选址的合理性,同时为了能够保障受灾地区应急物资的及时供应,以新型冠状病毒肺炎(COVID-19)疫情时期的湖北省为例,采用聚类-重心法对应急物流配送中心选址进行研究。首先,分别对受灾地区受灾程度、地理坐标及应急物资需求量进行聚类分析,并将两次聚类结果取交集后以受灾程度重为优先原则,确定二级应急物流配送中心的坐标;其次,分别以二级应急物流配送中心和受灾地区为依据,使用重心法分别求出一级应急物流配送中心Q和G的坐标;然后,以时间最短化为原则求出物流配送中心M的坐标;最后,结合周边环境和灾情状况将Q、G、M进行全面对比分析。结果表明:选择Q作为最终一级应急物流配送中心是最为合理的,这也证明综合考虑受灾地区受灾程度、地理坐标、应急物资需求量以及物流成本的聚类-重心法的应急物流配送中心选址模型具备现实可行性。

To ensure the rationality of the location of emergency logistics distribution center and ensure the timely supply of emergency supplies in the affected area,Hubei province during the outbreak of COVID-19 was taken as an example to study the location selection of emergency logistics distribution center by using the clustering-center of gravity method.First of all,clustering analysis was carried out based on the affected degree,geographical coordinates and emergency supply demand in the affected areas,and the coordinate of second-level emergency logistics distribution centers were determined according to the priority of affected degree based on the intersection of the two clustering results.Secondly,based on the second-level emergency logistics distribution centers and affected area,the center of gravity method was used to calculate the coordinates of first-level emergency logistics distribution center Q and G.Then,the coordinate of the logistics distribution center M under the principle of time minimization was solved.Finally,Q,G and M were comprehensively compared and analyzed in combination with the surrounding environment and the real affected situation.Results showed that it was reasonable to determine Q as the final first-level emergency logistics distribution center,which proved that the clustering-center of gravity method of emergency logistics distribution center location selection model with comprehensive consideration of affected degree,geographical coordinates,emergency supply demand and logistics cost had practical feasibility and advantages.