A strategic planning model for the railway system accident rescue problem

The present study examines the location of emergency rescue problems for urban ambulance and railway emergency systems. The proposed model considers probabilistic rescue demand, independent busy fractions of ambulances, and the corresponding risk levels in railway segments. We formulate the proposed model using fuzzy multi-objective programming and solve it using a generic algorithm and a non-dominated sorting genetic algorithm-II. Computation results are analyzed by applying the model to a real-world Taiwan railway system. Analytical results demonstrate that a proper adjustment of the rescue resource location improves rescue effectiveness for railway rescue and urban medical service demand.