Synergistic Optimization Method for URT Network Train Connection Scheme in Peak and Off-Peak Periods

• Published in: Journal of advanced transportation Vol. 2022; pp. 1 - 15
• Main Authors: Xu, Ruihua, Song, Xuyang, Zhou, Feng, Wang, Fangsheng
• Format: Journal Article
• Language: English
• Published: London Hindawi 20.10.2022; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Automatic fare collection; Case studies; Collaboration; Genetic algorithms; Light rail transit; Mathematical models; Methods; Operating companies; Operating costs; Optimization; Optimization models; Passengers; Peak periods; Railway stations; Simulation; Transfer stations; Transportation; Urban rail
• ISSN: 0197-6729; 2042-3195
• DOI: 10.1155/2022/6431231

In this study, we developed a method for coordinating and optimizing the train connection plans of different lines under the conditions of urban rail transit (URT) network operation. The method allows trains of different lines to form good connections at transfer stations, which can shorten the waiting time of passengers for transfers and reduce passenger retention. A mathematical model was developed to simulate the interaction between passengers and trains. Two optimization models were developed for the train connection plan of network transfer stations based on different optimization objectives during peak and off-peak hours. Subsequently, a corresponding solution method based on a genetic algorithm and simulation was designed. Finally, the Suzhou URT network was used as a case study, and the passenger flow of the transfer station was simulated and calculated using relevant automatic fare collection (AFC) data. The results indicated that the average waiting time and the number of passengers stranded were reduced using the proposed method. The calculation example demonstrated the effectiveness of the model and algorithm, which can guide the coordinated preparation of a network train connection plan.