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Last train timetable optimization for metro network to maximize the passenger accessibility over the end-of-service period
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Fang Wen, Yun Bai, Xin Zhang, Yao Chen, Ninghai Li
Railway Sciences | 2023, 2(2) : 273 - 288
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Railway Sciences | 2023, 2(2): 273-288
Research paper
Last train timetable optimization for metro network to maximize the passenger accessibility over the end-of-service period
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Fang Wen, Yun Bai, Xin Zhang, Yao Chen, Ninghai Li
Affiliations
  • Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China
  • Government Service Center of Beijing Municipal Transport Commission, Beijing Boats Inspection Center, Beijing, China
  • Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China
Published: 2023-06-10 doi: 10.1108/RS-03-2023-0012
Outline
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Purpose

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

Design/methodology/approach

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

Findings

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Originality/value

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

Urban rail transit  /  Last train of metro  /  Timetable optimization  /  End-of-operation period  /  Passenger demand  /  OD reachability
Fang Wen, Yun Bai, Xin Zhang, Yao Chen, Ninghai Li. Last train timetable optimization for metro network to maximize the passenger accessibility over the end-of-service period[J]. Railway Sciences, 2023 , 2 (2) : 273 -288 . DOI: 10.1108/RS-03-2023-0012
  • Talents Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities(2021RC228)
  • Special Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities(2021YJS103)
Year 2023 volume 2 Issue 2
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Article Info
doi: 10.1108/RS-03-2023-0012
  • Receive Date:2023-03-12
  • Online Date:2026-06-11
  • Published:2023-06-10
Article Data
Affiliations
History
  • Received:2023-03-12
  • Revised:2023-05-04
  • Accepted:2023-05-09
Funding
Talents Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities(2021RC228)
Special Funds for Basic Scientific Research Business Expenses of Central Colleges and Universities(2021YJS103)
Affiliations
    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China
    Government Service Center of Beijing Municipal Transport Commission, Beijing Boats Inspection Center, Beijing, China
    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

Corresponding:

Yao Chen can be contacted at:
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表12种不同金属材料的力学参数

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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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