Line optimization of urban rail transit network based on improved kruskal algorithm

The optimization of urban rail transit network routes is of great significance for ensuring efficient operation of urban transportation and promoting sustainable development of cities. Therefore, a line optimization method of urban rail transit network based on improved Kruskal algorithm is proposed. Firstly, the Kruskal algorithm is improved through a candidate path selection method based on weight modification, and the improved Kruskal algorithm is used for urban rail transit network partitioning, Then, combining the division results with the average travel cost, accessibility, and robustness of passengers, a route optimization objective function is constructed, Finally, the adaptive genetic algorithm is used to solve the optimization objective function, and the optimal solution can be obtained by chromosome decoding operation. The experimental results show that the coverage rate of the proposed method in the rail transit network is always above 75.7%, with a maximum punctuality rate of 99.36% and a cost-effectiveness ratio of 0.81.