School of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei, China.
PLoS One. 2023 Mar 23;18(3):e0282796. doi: 10.1371/journal.pone.0282796. eCollection 2023.
In recent years, the frequent occurrence of public health emergencies has had a significant impact on people's life. The study of emergency logistics has also attracted scholars' attention. Therefore, matching emergency materials' supply and demand quickly, which meets urgency and satisfaction, is the purpose of this paper. This paper used the Metabolism Grey Model (1,1) (GM (1,1)) and the material demand prediction model to predict the number of infections and material demand. Besides, we established a bi-objective optimization model by constructing a profit and loss matrix and a comprehensive utility perception matrix. The results show that the method is helpful in matching the optimal supply and demand decision quickly on the basis of meeting urgency and satisfaction. The method is helpful in improving the fairness of emergency material distribution, which could better protect people's livelihoods.
近年来，公共卫生突发事件频繁发生，对人们的生活产生了重大影响。应急物流的研究也引起了学者们的关注。因此，快速匹配应急物资的供需，满足紧迫性和满意度，是本文的目的。本文采用新陈代谢灰色模型（1,1）（GM（1,1））和物资需求预测模型预测感染人数和物资需求。此外，我们通过构建损益矩阵和综合效用感知矩阵建立了一个双目标优化模型。结果表明，该方法有助于在满足紧迫性和满意度的基础上快速匹配最优的供需决策。该方法有助于提高应急物资分配的公平性，更好地保护民生。
