Determination of the Skip-Stop Scheduling for a Congested Transit Line by Bilevel Genetic Algorithm
This study focuses on how to determine the skip-stop scheduling for a congested urban transit line during the morning rush hours. A transit schedule with uneven headways and skip-stop operations is adopted to match the time-dependent demands and accelerate the circulative utilizations of vehicles. This schedule allows the buses to run on unequal vehicle-departure intervals and to skip some stations. A nonlinear programming model is formulated to minimize the overall waiting times and the in-vehicle crowded costs subjected to a limited number of vehicles. According to the layered characteristics of the skip-stop scheduling, a bilevel genetic algorithm is developed to solve the proposed model. The possible departure times of vehicles at the terminal are searched by the outer genetic algorithm and the skip-stop operations are solved by the inner genetic algorithm. Finally, the proposed model and algorithm are successfully tested with the help of a real-world case.
bilevel genetic algorithm transit scheduling skip-stop operation optimization