Research on Tobacco Retail Store Regulatory Route Optimization Algorithm Based on Graph Attention Mechanism for Node Selection
Since the tobacco retail stores in cities are dense,traditional path planning algorithms for solving the optimal supervision path will consume a lot of time,and cannot guarantee the effect within the specified time.In addition,existing methods seldom consider the network characteristics and the explainability of the candidate subset.This study proposes a graph attention-based node selection and path optimization algorithm(GA-SGPO),which iteratively selects the optimal coordinate node subset and performs calculation on the subset to reduce computa-tion time.In addition,the structural similarity between nodes is calculated to reduce the sparsity of training samples.The experimental data in-cludes the coordinates of 40,000 retail stores in Dongguan City.The experimental results show that the GA-SGPO model ensures the solution accuracy while the solution time is reduced by an average of 48%.The GA-SGPO can significantly save computational time and is closer to practical application scenarios.The attention mechanism and node similarity calculation can provide visualization basis for optimal node selec-tion.
万方数据
维普
