A Benders Decomposition Algorithm for the Passenger Train Service Planning. (9th February 2021)

• Record Type: Journal Article
• Authors: Pu, Song
• Other Names: Gao Yuan Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2021(2021)
• Publication Date: 2021-02-09
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2021/6653334
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : Railway transport becomes a more popular transportation in many countries due to its large transport capacity, low energy consumption, and benign environment. The passenger train service planning is the key of the rail operations system to balance the transport service and the passenger demand. In this paper, we propose a mixed binary linear programming formulation for the passenger train service planning to optimize the train route, frequency, stop schedule, and passenger assignment simultaneously. In addition, we analyze the computational complexities of the model and develop a Benders decomposition algorithm with valid inequalities to solve this problem. Finally, our model and algorithm are tested on a real-world instance of the Beijing-Shanghai high-speed railway line. The computational results show that our approach can solve these problems within reasonable solution time and small optimality gaps (less than 2.5%).