Optimizing the draft passenger train timetable based on node importance in a railway network

ABSTRACT

Train timetable plays an important role in the passenger train operations, which is typically developed or adjusted from the draft train timetable (DTT). The DTT serves as the basic framework and the core component of the train timetable to generate the rough plan of passenger trains, and eventually impacts the performance of the train operations. The paper attempts to develop a draft passenger train timetable under the constrained capacities of arrival–departure tracks and servicing tracks for the passenger train coaching stocks in a passenger railway network. The goals of the DTT are to satisfy the expected arrival/departure time, reduce the number of passenger coaching stocks, and avoid the closely spaced arrival/departure times. We propose a heuristic optimization algorithm based on the node importance to calculate the optimal train arrival and departure times at each arrival/departure station. The proposed model and algorithm are demonstrated in an experimental network with 11 stations and 73 trains in China; the results show that 93.06% of the trains can utilize the minimum passenger coaching stocks, and the equilibrium among passenger trains of the same route daily are improved approximately 20% compared to the actual timetable.

KEYWORDS:

• Draft train timetable
• node importance
• heuristic strategy
• fuzzy set
• railway network

Acknowledgment

The authors thank the associate editor and two anonymous reviewers for their insightful comments.