Emergency Logistics Distribution Center Location Model Based on ISG-IAGNES Clustering and Symmetrical IDFS Spatial Decision Tree Algorithm

Taking emergency logistics scenarios under urban public emergencies as the research background, this paper analyzes the current research status and existing problems of distribution center location methods. It constructs an emergency logistics distribution center location model based on ISG-IAGNES clustering and a symmetrical IDFS spatial decision tree algorithm. Firstly, the ISG spatial model is constructed to divide urban geographic space into cellular units and then topologically generate the cellular space. Secondly, the IAGNES algorithm is established to achieve cellular space clustering, realizing the dimensionality reduction operation of the urban emergency space. Thirdly, the symmetrical characteristic of the pathway is taken as the core condition to construct the DFS algorithm to build the graph global searching model, and then the logistics distribution center location model based on the symmetrical IDFS spatial decision tree algorithm is constructed. The experiment proves that the optimization rate of the distribution center selected by the proposed algorithm in terms of route distance cost and time cost is 9.82% compared to the centroid method and analytic hierarchy process, 14.41% compared to the Dijkstra algorithm, and 17.21% compared to the Prim algorithm. It proves that the proposed algorithm has advantages over traditional algorithms in reducing the distance cost and time cost of logistics routes.