Resilience Assessment and Optimization for Urban Rail Transit Networks: A Case Study of Beijing Subway Network
With the rapid development of urban rail transit, huge subway systems have been built, which is the best choice for people due to the efficiency, safety, and punctuality. Therefore, the ability of subway systems to resist failures especially interruptions has attracted the attention of operators. In the paper, based on the graph theory, a resilience assessment method is proposed to quantitatively measure the performance and recovery rapidity within unifying metrics and models. We represent the subway network with an undirected graph where the subway stations are described using the nodes whereas tracks are demonstrated with the edges. The performance evaluation of a subway network is implemented based on the assessment of passenger flow and topological structure of the network, where weighted degrees and the weighted sum of the reasonable passageway to the other nodes are considered. The resilience of a subway network can be associated to the network performance loss triangle over the relevant timeline from the occurrence of a random or intentional disruption to full recovery. The Beijing Subway is taken as the example to perform the proposed approach which is verified through the numerical results in the paper. Following the resilience evaluation, a structure optimization model with a computational algorithm is proposed. Based on the genetic algorithm, we achieved the solution results of the simplified network of the Beijing Subway. Several interesting conclusions are drawn from the results.
IEEE Access