Optimization of energy-efficiency train schedule considering passenger demand and rolling stock circulation plan of subway line

An energy-efficiency train schedule greatly contributes to alleviating some environmental issues such as carbon emissions. However, the pursuit of reducing train energy consumption often leads to passengers' longer travel time, and more operation cost of rolling stocks. Thus, it is necessary to consider costs of passengers and rolling stocks when optimizing the energy-efficiency schedule for better satisfying passenger demand and reducing trains' total operating cost. In this paper, a mixed integer nonlinear programming model of energy-efficiency train schedule considering passenger demand and rolling stock circulation plan is established for minimizing passengers' travel cost and trains' operating cost. More specifically, this model devotes to simultaneously optimizing: (1) passengers' travel choices to reduce passengers’ waiting time and travel time, (2) the selection of train traction strategy in the section to reduce the traction energy consumption, and (3) the train connection scheme to ensure the economy of the rolling stock circulation plan. This paper designs a variable neighborhood search algorithm combined with CPLEX solver to solve the model efficiently. Based on the data of Guangzhou Metro Line 9, the optimization method proposed in this paper can reduce the train operation cost by 9.73% and the total passenger travel cost by 18.11%.