HighlightsA bi-level model with consideration of passengers' adjusting behavior is proposed.The capacity of trains is considered as an explicit constraint in the model.A genetic algorithm incorporating the method of successive averages is introduced.Two numerical examples and a real case are employed to validate the bi-level model.Sensitivity analyses show the impact of desired arrival time and crowding.
AbstractThis paper proposes abi-level model to solve the timetable design problem for an urban rail line. The upper level model aims at determining the headways between trains to minimize total passenger cost, which includes not only the usual perceived travel time cost, but also penalties during travel. With the headways given by the upper level model, passengers’ arrival times at their origin stops are determined by the lower level model, in which the cost-minimizing behavior of each passenger is taken into account. To make the model more realistic, explicit capacity constraints of individual trains are considered. With these constraints, passengers cannot board a full train, but wait in queues for the next coming train. A two-stage genetic algorithm incorporating the method of successive averages is introduced to solve the bi-level model. Two hypothetical examples and a real world case are employed to evaluate the effectiveness of the proposed bi-level model and algorithm. Results show that the bi-level model performs well in reducing total passenger cost, especially in reducing waiting time cost and penalties. And the section loading-rates of trains in the optimized timetable are more balanced than the even-headway timetable. The sensitivity analyses show that passenger’s desired arrival time interval at destination and crowding penalty factor have a high influence on the optimal solution. And with the dispersing of passengers' desired arrival time intervals or the increase of crowding penalty factor, the section loading-rates of trains become more balanced.
A bi-level model for single-line rail timetable design with consideration of demand and capacity
Tramsportation Research, Part C: Emerging Technologies ; 85 ; 211-233
2017-09-03
23 pages
Article (Journal)
Electronic Resource
English
Circle rail transit line timetable scheduling using Rail TPM
British Library Conference Proceedings | 2010
|Effects of timetable related service quality on rail demand
Elsevier | 2016
|Demand-driven timetable and stop pattern cooperative optimization on an urban rail transit line
Taylor & Francis Verlag | 2020
|THE PERIODIC TIMETABLE INFLUENCE ON LINE CAPACITY
TIBKAT | 2018
|Demand-driven timetable design for metro services
Elsevier | 2014
|