Increasing the resilience level of a vulnerable rail network: The strategy of location and allocation of emergency relief trains

This paper examines the optimal location and allocation of relief trains (RTs) to enhance the resilience level of the rail network. Unlike probabilistic approaches, the priority of demand is handled by link exposure measure which considers the operational attributes of links and accessibility to road system. We formulate the proposed model using a bi-objective programming and solve it using an augmented e-constraint method (AUGMECON) combined with a fuzzy-logic approach. The proposed framework is employed to a real-world case study, and analytical results reveal the superiority of the proposed model in providing an economical and effective layout compared to conventional maximal covering model.