Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors
Chuntian Zhang,
Yuan Gao,
Lixing Yang,
Uday Kumar and
Ziyou Gao
Omega, 2019, vol. 87, issue C, 86-104
Abstract:
Regular maintenances on high-speed railway facilities are performed in every night in China, and during regular maintenances, high-speed railway is not available for the sunset-departure and sunrise-arrival trains (SDSA-trains). In order to reduce the influence of regular maintenances on SDSA-trains, three operation modes are used in practice, which mainly consist of route selections between high-speed railway and normal-speed railway. In this paper, we use some linearization techniques to formulate a mixed integer linear programming (MILP) model to identify the operation modes and the timetable of SDSA-trains, by integrating the time window selection of regular maintenances on high-speed railways. The objective of the model is to minimize the total travel time of SDSA-trains. In the formulation of the model, we introduce state variables to indicate whether a train is running on high-speed railway or not, which makes it conveniently express the selection of operation modes. Based on the real data of Beijing-Guangzhou high-speed and normal-speed railway corridors in China, numerical experiments are carried out to test the proposed model and optimization method.
Keywords: Train scheduling; Maintenance planning; High-speed railway; Sunset-departure and sunrise-arrival train (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305048317310575
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:87:y:2019:i:c:p:86-104
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.omega.2018.08.005
Access Statistics for this article
Omega is currently edited by B. Lev
More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().