Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm

Abstract EN

As a sustainable transportation mode, high-speed railway (HSR) has been developing rapidly during the past decade in China.

With the formation of dense HSR network, how to improve the utilization efficiency of train-sets (the carrying tools of HSR) has been a new research hotspot.

Moreover, the emergence of railway transportation hubs has brought great challenges to the traditional train-sets’ utilization mode.

Thus, in this paper, we address the issue of train-sets’ utilization problem with the consideration of railway transportation hubs, which consists of finding an optimal Train-set Circulation Plan (TCP) to complete trip tasks in a given Train Diagram (TD).

An integer programming TCP model is established to optimize the train-set utilization scheme, aiming to obtain the one-to-one correspondence relationship among sets of train-sets, trip tasks, and maintenances.

A genetic algorithm (GA) is designed to solve the model.

A case study based on Nanjing and Shanghai HSR transportation hubs is made to demonstrate the practical significance of the proposed method.

The results show that a more efficient TCP can be formulated by introducing train-sets being dispatched among different stations in the same hub.