Considering the dynamics and uncertainty of passenger and freight demand, this paper proposes an optimization method of rolling stock circulation plan for passenger-freight co-transportation. Based on the flexible composition mode, a twostage stochastic programming model is proposed. The first stage considers the constraints of train composition and rolling stock circulation plan, with the objective of minimizing the train operation cost. The second stage considers the rules of passenger and cargo flow allocation, with the objective of minimizing the delay time of cargo groups and the number of passenger delays. A series of numerical experiments based on the Beijing Subway Yizhuang line are implemented to show the effectiveness of the proposed method, which are solved by Gurobi and variable neighborhood descent (VND) algorithm. The results show that in comparison with the fixed composition mode, the flexible composition mode can better cope with the uncertainty of demand, which can reduce the train operation cost and improve the quality of transportation service.
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