Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model

At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sec...

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Vydáno v:Sustainability Ročník 11; číslo 13; s. 3701
Hlavní autoři: Xue, Qiuchi, Yang, Xin, Wu, Jianjun, Sun, Huijun, Yin, Haodong, Qu, Yunchao
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.07.2019
Témata:
Construction costs
Efficiency
Energy consumption
Integer programming
Optimization
Passengers
Quality of service
Routing
Schedules
Suburban areas
Sustainability
Traffic congestion
ISSN:2071-1050, 2071-1050
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Shrnutí:At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sections, resulting in a waste of capacity. In view of this situation, this paper develops a nonlinear integer programming model to determine an optimal timetable with a balanced scheduling mode, where the wasted capacity at a constant departure frequency can be reduced with a slight increase in passenger waiting time. Then, we simplify the original model into a single-objective integer optimization model through normalization. A genetic algorithm is designed to find the optimal solution. Finally, a numerical example is presented based on real-world passenger and operation data from Beijing Metro Line 4. The results show that the double-routing optimization model can reduce wasted capacity by 9.5%, with a 4.5% increase in passenger waiting time, which illustrates the effectiveness of this optimization model.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2071-1050
2071-1050
DOI:10.3390/su11133701