Optimizing train operational plan in an urban rail corridor based on the maximum headway function. (January 2017)

• Record Type: Journal Article
• Authors: Shi, Feng; Zhao, Shuo; Zhou, Zhao; Wang, Pu; Bell, Michael G.H.
• Is Part Of: Transportation research. Volume 74(2017)
• Page Start: 51
• Page End: 80
• Publication Date: 2017-01
• Subjects: Urban rail corridor -- Train operational plan -- Maximum headway function -- Time-varying demand -- Optimization algorithm; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2016.11.007
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Propose the optimization of the train operational plan in an urban rail corridor. Develop the formulation of maximum headway function. Decompose the problem into two sub-problems. Design two efficient algorithms with linear computational complexity. Abstract: The train operational plan (TOP) plays a crucial role in the efficient and effective operation of an urban rail system. We optimize the train operational plan in a special network layout, an urban rail corridor with one terminal yard, by decomposing it into two sub-problems, i.e., the train departure profile optimization and the rolling stock circulation optimization. The first sub-problem synthetically optimizes frequency setting, timetabling and the rolling stock circulation at the terminal without a yard. The maximum headway function is generated to ensure the service of the train operational plan without considering travel demand, then we present a model to minimize the number of train trips, and design a heuristic algorithm to maximize the train headway. On the basis of a given timetable, the rolling stock circulation optimization only involves the terminal with a yard. We propose a model to minimize the number of trains and yard–station runs, and an algorithm to find the optimal assignment of train-trip pair connections is designed. The computational complexities of the two algorithms are both linear. Finally, a real case study shows that the train operational plan developed by our approach enables a better match of train headway and travel demand, and reduces the operational cost while satisfying the requirement of the level of service.