物流配送需求的不确定性导致物流配送成本波动，增加了物流企业配送管理的难度，加剧了“最后一公里”末端配送不畅。以降低末端物流配送成本和缩短配送时间为优化目标，考虑快递包裹数量不确定情况下末端配送的运力水平和配送覆盖区域人口密度因素，提出了一种基于“0-1”整数规划模型的多重目标优化策略，建立了物流配送中心的动态选址模型，并用Anylogic进行了仿真验证。研究结果表明，在配送包裹数量短期大幅度波动的情况下，末端配送运力水平、网点位置和服务能力需要有差别调整才能达到降本增效的目的。

The uncertainty of logistics distribution demands leads to fluctuations in logistics delivery costs, which increases the difficulty of logistics management and exacerbates the inefficiency of the "last mile" delivery. Aiming to reduce the costs and shorten the delivery time of last-mile logistics, a multi-objective optimization strategy based on a "0-1" integer programming model was proposed, considering the transportation capacity and population density of the service area under uncertain package volumes. A dynamic location model for logistics distribution centers was established and validated through simulation using Anylogic. The results of the study indicate that, in the case of significant short-term fluctuations in the number of packages to be delivered, differentiated adjustments in the level of transportation capacity, outlet locations, and service capabilities are necessary to achieve cost reduction and efficiency enhancement.