A method to improve the resilience of multimodal transport network: Location selection strategy of emergency rescue facilities

This paper studies the location selection strategy of emergency rescue facilities in the multimodal transport network to improve the resilience of the network. Based on the overall perspective, we propose a cooperative coverage model. On one hand, it helps network operators improve the recovery speed of the entire multimodal transport network in the event of a disaster. On the other hand, it maximizes the effect of the rescue cost of government managers. But we must note that in most transport networks, failure data is difficult to be collected or is insufficient. Therefore, we propose the premise that the network failure may occur at any point. The rescue demand is quantified by the links/nodes importance, which is calculated by the multi-attribute decision-making method based on hesitant intuitionistic fuzzy set-technique for order preference by similarity to an ideal solution (TOPSIS). Then, a multi-objective non-linear programming model is established, and fast non-dominated sorting genetic algorithm-cellular automata (NSGA-II-CA) is designed to solve the model. Taking the multimodal transport network in the Sichuan-Tibet region of China as an example, calculation and analysis are performed to verify the effectiveness and advancement of the proposed model and algorithm. The innovation of this paper is to propose a method of emergency rescue facility location from the perspective of global optimization.

Automated summary

This paper investigates the location selection strategy of emergency rescue facilities in the multimodal transport network to enhance network resilience. A cooperative coverage model and a multi-objective non-linear programming model are proposed and validated through calculations and analysis. The innovation lies in proposing an emergency rescue facility location method from a perspective of global optimization.