Due to the advantages of high punctuality and speed, urban rail transit systems are attracting more and more commuters. In consequence, overcrowding during peak periods has become the norm in megacities, which poses a great challenge to operations. To address this challenge, this paper investigates the integrated optimization of passenger flow control and bus-bridging on oversaturated urban rail transit lines. Based on the time-dependent passenger demand, we propose an integer nonlinear programming model that aims to minimize the overall system cost. Then, to cope with the solving difficulty due to nonlinearity, the proposed formulation is further transformed into an equivalent mixed-integer linear programming model. Finally, real-world case studies based on the operating data of Beijing metro Batong line are applied to verify the effectiveness of our proposed approach. The computational results illustrate that our proposed method can significantly reduce the average passenger waiting time and improve operational safety.
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