The uncertainty and sudden nature of public health emergencies make efficient and accurate emergency material allocation plans particularly important.A site selection model of daily necessities distribution transfer station under the background of public health emergencies was constructed.Considering the occurrence of special events and updating priority coefficients and time window calculations,a multi-objective delivery path planning model was established using transportation distance,penalty cost for violating vehicle capacity and time window constraints as the optimization goals.The site selection problem was solved by the K-means clustering algorithm and the optimal delivery path was obtained using a hybrid genetic algorithm combining genetic algorithm and large neighborhood search algorithm.Finally,the example of material distribution in the Chaoyang District of Changchun was used to empirical analysis.The results indicate that 200 neighborhoods can be clustered into 60 material demand sites for distribution.It requires 26 vehicles to transport the materials from the distribution center to the demand sites and four types of optimal material distribution schemes are obtained,which provides a new idea for solving the emergency material allocation under public health emergencies.
关键词
物资调配/路径规划/多目标/K-means聚类算法/混合遗传算法
Key words
material allocation/path planning/multi-objective/K-means clustering algorithm/hybrid genetic algorithm
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