Collaborative passenger flow control for oversaturated metro lines: a stochastic optimization method
Document Type
Journal Article
Publication Date
2022
Subject Area
place - urban, mode - subway/metro, ridership - demand, planning - methods, planning - travel demand management, planning - safety/accidents, planning - service improvement
Keywords
Passenger flow control, stochastic and dynamic passenger demand, integer linear programming, Lagrangian relaxation
Abstract
With the rapid increase in travel demands in urban areas, large passenger flow becomes a common phenomenon in the metro system of some large cities. To ensure the safety and improve the operational efficiency of the metro system, this paper proposes an effective method to formulate a robust passenger flow control strategy over a metro line, in which the stochastic and dynamic passenger flow is specifically considered. By discretizing the time horizon into a series of time intervals, we propose an integer linear programming model aimed at minimizing the expected passenger waiting time over the metro line. To solve the proposed model, a heuristic algorithm that integrates the Lagrangian relaxation approach and CPLEX solver is designed to search for high-quality solutions for the problem of interest. Finally, two sets of numerical experiments, including a small-scale case and a real-world instance, are implemented to validate the performance of the proposed approaches.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Meng, F., Yang, L., Shi, J., Jiang, Z., & Gao, Z. (2022). Collaborative passenger flow control for oversaturated metro lines: a stochastic optimization method. Transportmetrica A: Transport Science, Vol. 18(3), pp. 619-658.
