Group-based railway seat allocation policies considering the risk of virus transmission

Abstract

To mitigate the transmission risk of infectious diseases (e.g., COVID-19) on trains while maintaining a certain level of railway service and improving railway operation revenue, this study proposes a passenger group-based railway seat allocation policy. First, the shedding rate is used to estimate the risk of virus transmission among passenger groups (different infectious diseases can be treated in a similar manner). Then, a mixed integer programming model is established, which minimizes the summation of shedding rates and maximizes the railway operation revenue. In the proposed policy, both virus diffusion between cities associated with different risk levels and virus transmission among different passenger groups in train carriages are considered. A tailored heuristic algorithm based on the multi-start variable neighborhood search (M-VNS) algorithm is then designed to quickly produce a high-quality solution for practical large-scale applications. A series of numerical studies are conducted, demonstrating the efficacy of the proposed policy in enhancing railway revenue and mitigating the (estimated) transmission risk of infectious disease.