基于聚类和免疫算法优化物资管理分配

Optimized Material Management Distribution Based on Clustering and Immune Algorithms

摘要: 本文在生活物资管理的科学发放问题中以优化生活物资投放点的位置和数量，减少投放物资需要的人力指标为目标构建相应的数学模型，为紧急安全事件中大规模封控情况下居民生活物资配送提供预案。为了实现较好的分配结果，我们建立模型计算出各区合理的投放点数量、大规模物资分拣场所数量，通过K-means聚类选出大规模物资分拣场和投放点的地址，使用免疫算法优化配送路径，得出最优分配方案。结果表明该模型能有效解决突发事件中物资分配管理问题，为公共物资资源配置管理提供了新的解决思路。

Abstract: In the scientific issuance of living materials management, this article uses the position and quantity of the placement point of life materials, and reduces the human indicators required for the need for the launch. Delivery provides a plan. In order to achieve good distribution results, we establish a model to calculate the number of reasonable launch points in each district and the number of large-scale material sorting places, select the address of the large-scale material sorting site and the address of the launch point through the K-MEANS cluster, and use the immune to use the immunity, and use the immunity to use the immunity. The algorithm optimizes the delivery path to obtain the optimal allocation scheme. The results show that the model can effectively solve the management of material distribution in emergencies, and provides new solutions for the management of public materials resource allocation.