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Railway transportation plays an important role in many disaster relief and other emergency supply chains. Based on the analysis of several recent disaster rescue operations in China, the paper proposes a mathematical model for emergency railway wagon scheduling, which considers multiple target stations requiring relief supplies, source stations for providing supplies, and central stations for allocating railway wagons. Under the emergency environment, the aim of the problem is to minimize the weighted time for delivering all the required supplies to the targets. For efficiently solving the problem, we develop a new hybrid biogeography-based optimization (BBO) algorithm, which uses a local ring topology of population to avoid premature convergence, includes the differential evolution (DE) mutation operator to perform effective exploration, and takes some problem-specific mechanisms for fine-tuning the search process and handling the constraints. Computational experiments show that our algorithm is robust and scalable, and outperforms some state-of-the-art heuristic algorithms on a set of problem instances.