Integrated optimization of line planning and train timetabling in railway corridors with passengers' expected departure time interval. (December 2021)

• Record Type: Journal Article
• Authors: Zhang, Chuntian; Qi, Jianguo; Gao, Yuan; Yang, Lixing; Gao, Ziyou; Meng, Fanting
• Is Part Of: Computers & industrial engineering. Volume 162(2021)
• Publication Date: 2021-12
• Subjects: Line planning -- Train timetabling -- Integrated optimization -- Time-related passenger demand; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107680
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We jointly optimize the line plan and train timetable. The expected departure time interval of passenger is considered. A MILP model is formulated for the proposed problem. Several numerical experiments are implemented to show effectiveness of approaches. Abstract: Line planning and train timetabling are two basic problems in railway operations. A commonly used way is to first obtain the line plan and then design the train timetable based on the pre-generated line plan. This paper expects to find an effective way to combine these two problems into an integrated optimization model, in which the line plan and timetable are optimized simultaneously. Specifically, with the help of some linearization techniques, we formulate a mixed integer linear programming (MILP) model to find the optimal number of operated trains, as well as the origin and destination stations, stop plan, arrival/departure times of each train at each station and assignment of passenger demands on each train, by employing the railway corridor information and time-related passenger demands as inputs. We aim to simultaneously minimize the operation cost and total travel time of trains, and the bi-objective problem is effectively transformed into a single-objective problem by linear weighted methods. Finally, a series of numerical experiments based on Wuhan-Guangzhou high-speed railway corridor in China verify the effectiveness of the integrated optimization methods.