Optimization of Train Operation Plans for Urban Rail Transit Based on Platform Crowding Degree - WANG Yeliu; LIU Yong; LIANG Ye (Kongzhi Yu Xinxi Jishu)
In order to enhance passenger travel experience, align transportation capacities with demands, and alleviate platform overcrowding at metro stations, this paper proposes a methodology for optimizing train operation plans based on platform crowding degree in rail transit systems, as a result of studies focusing on optimizing multi-route train operation plans based on historical passenger flow demands and automatically scheduling multi-route train operation for these systems. First, a modeling analysis was performed using historical sectional passenger flow and origin-destination (OD) passenger flow data, prioritizing platform overcrowding degree. A multi-objective integer planning model was constructed for the multiple-route operation of trains, aiming to minimize the maximum platform crowding degree and achieve the optimal match between train capacities and transportation volumes. Next, a genetic algorithm was utilized to derive the optimal operation plan through a solving process, and this optimal plan was integrated into subsequent operation scheduling, facilitating the automatic compilation of multi-route operation schedules. Finally, the effectiveness of the proposed approach was validated through simulations based on historical passenger flow data from a rail transit line. The simulation results indicated that the automatically-compiled multiple-route operation schedules based on this method lowered the maximum platform crowding degree by 20.6%, compared to manually-compiled ones, highlighting the algorithm's value in practical applications.