【摘要】 疫情高发期间将社区根据感染情况分3种类型：无感染区、零星偶发区、疫区。疫情高发期间由于物流配送延迟而导致的物资假性短缺，容易造成市民恐慌抢购心理。为防止此类情形发生，将配送点根据疫情的情况也分成3类，优先配送疫情严重的区域。考虑配送优先级、消毒时间等因素，构建物流成本、配送时间窗惩罚以及生鲜产品价值流失加权和为优化目标的混合整数规划模型。用交叉变异改进磷虾觅食优化算法来求解该模型。通过数值算例进行虚拟仿真，研究结果表明，模型和算法是合理有效的，可为疫情下物流企业的配送提供一定参考和决策支持。更多还原

【Abstract】 During the epidemic, communities or towns were divided into three types according to the infection situation: no infection area, sporadic area and epidemic area. The fake shortage of commodities caused by the delay of delivery can easily cause public panic. In order to prevent such situations, the distribution points will be divided into three categories according to the situation of the epidemic, giving priority to the areas with serious epidemics. Considering factors such as distribution priority and disinfection time, a mixed integer programming model with logistics cost, distribution time window penalty, and weighted sum of fresh commodity value loss as optimization goals is constructed. Then, according to the characteristics of the model, the krill herd optimization algorithm with cross mutation to solve the model. Finally, through the numerical simulation experiment, the results show that the model and algorithm are reasonable and effective, which can provide some reference and decision support for the distribution of goods by logistics enterprises under the epidemic situation.更多还原