Abstract

The time passengers spending on waiting at transfer stations is one of crucial criteria which measures the quality of public transit service. Regional public transportation timetable synchronization can reduce the transfer waiting times so that improve the service quality. As a result, this paper presents a mixed integer nonlinear programming model for public transit schedule synchronization problem with the objective of minimizing transfer waiting times. The model includes the weights of transfer stations and a specific delay which most of the vehicles can expect due to the uneven passenger flow at transfer stations and road congestion during rush hours. Then, the proposed model is expanded to a second model which optimized the stopping time based on the necessary time in order to avoid just missing the connecting vehicles. Finally, a genetic algorithm approach is presented by considering the characteristics of the models and applied into a case study. The computational results demonstrate that the proposed models and the genetic algorithm approach are efficient and feasible.

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