A network-based approach to improving robustness of a high-speed train by structure adjustment

To enhance the ability of a high-speed train (HST) to provide services under various adverse conditions, this paper studies robustness improvement of the HST by adjusting its structure. We model the HST as an interdependent machine-electricity-communication network (IMECN) composed of a machine network (MN), an electricity network (EN) and a communication network (CN), and propose a robustness metric of the IMECN subject to node failures considering failure propagation. Then, a robustness optimization model is constructed for structure adjustment. A Tabu search algorithm with directed and undirected edge exchange operators is designed to solve this problem. A case study on a practical HST is used to verify the feasibility and effectiveness of the proposed method. The results show that robustness of the IMECN is significantly improved by structure adjustment. Furthermore, most nodes have little effect on robustness, and impact of failures on any node is minimized after optimization. In addition, in terms of topology, nodes with low and high degrees in the MN and CN reconnect with those with a similar degree, their clustering coefficients become larger, and closeness of all nodes in the subnetworks increases. Finally, adjusting the structures leads to a slight difference of loads in the EN and CN.