突发公共卫生事件应急物资无接触式配送路径优化

Optimization of Contactless Distribution Path for Emergency Materials in Public Health Emergencies

为解决突发公共卫生事件下大批量应急物资配送问题,研究了“卡车-无人车”联合配送模式。针对多约束客户点聚类问题,设计了防止K值变动偶然性的改进K-means++聚类算法;根据紧迫度大的客户点优先配送的原则,提出2类客户点并行配送的无人车调度方案,构建以配送时间最短为目标的路径优化模型。结果表明:改进K-means++算法得到的聚类数量K更为稳定;相同聚类结果的情况下,改进多种群遗传算法迭代次数更少、最优解更佳;改进后的算法组合最优解远优于其他3种组合算法。

In order to solve the problem of high-volume emergency material distribution in public health emergencies,the joint distribution mode of"truck-unmanned vehicle"is studied.The improved K-means++clustering algorithm is designed to prevent the chance of K-value change for the multi-constrained customer point clustering problem.According to the principle of priority distribution of customer points with high urgency,an unmanned vehicle scheduling scheme of parallel distribution of two kinds of customer points was proposed,and a route optimization model aiming at the shortest distribution time is constructed.The results show that the number of clusters K obtained by the improved K-means++algorithm is more stable;the improved multiple population genetic algorithm has fewer iterations and better optimal solutions for the same clustering results;the combined optimal solution of the improved algorithm is much better than the other three combined algorithms.