Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/101284
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Civil and Environmental Engineering | - |
| dc.creator | Yang, X | en_US |
| dc.creator | Chen, A | en_US |
| dc.creator | Ning, B | en_US |
| dc.creator | Tang, T | en_US |
| dc.date.accessioned | 2023-08-30T04:16:29Z | - |
| dc.date.available | 2023-08-30T04:16:29Z | - |
| dc.identifier.issn | 1366-5545 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/101284 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Pergamon Press | en_US |
| dc.rights | © 2016 Elsevier Ltd. All rights reserved. | en_US |
| dc.rights | © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
| dc.rights | The following publication Yang, X., Chen, A., Ning, B., & Tang, T. (2017). Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty. Transportation Research Part E: Logistics and Transportation Review, 97, 22-37 is available at https://doi.org/10.1016/j.tre.2016.10.012. | en_US |
| dc.subject | Bi-objective | en_US |
| dc.subject | Energy consumption | en_US |
| dc.subject | Metro systems | en_US |
| dc.subject | Timetable optimization | en_US |
| dc.title | Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 22 | en_US |
| dc.identifier.epage | 37 | en_US |
| dc.identifier.volume | 97 | en_US |
| dc.identifier.doi | 10.1016/j.tre.2016.10.012 | en_US |
| dcterms.abstract | For optimization of timetables in metro systems with regular cyclic operation, this paper develops a bi-objective programming approach addressed to minimization of net energy consumption and total travel time with provision for dwell time uncertainty. Firstly, we formulate the bi-objective timetable optimization problem as an expected value model with speed profile control. Secondly, we use the ɛ-constraint method within a genetic algorithm framework to determine the Pareto optimal solutions. Finally, numerical examples based on the real-life operation data from the Beijing Metro Yizhuang Line are presented in order to illustrate the practicability and effectiveness of the approach developed in the paper. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Transportation research. Part E, Logistics and transportation review, Jan. 2017, v. 97, p. 22-37 | en_US |
| dcterms.isPartOf | Transportation research. Part E, Logistics and transportation review | en_US |
| dcterms.issued | 2017-01 | - |
| dc.identifier.scopus | 2-s2.0-84995768079 | - |
| dc.identifier.eissn | 1878-5794 | en_US |
| dc.description.validate | 202308 bcch | - |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | CEE-2286 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | National Natural Science Foundation of China; China National Funds for Distinguished Young Scientists; Beijing Municipal Science and Technology Commission; Fundamental Research Funds for the Central Universities | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 6697074 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Chen_Bi-objective_Programming_Approach.pdf | Pre-Published version | 1.13 MB | Adobe PDF | View/Open |
Page views
135
Last Week
0
0
Last month
Citations as of Nov 9, 2025
Downloads
128
Citations as of Nov 9, 2025
SCOPUSTM
Citations
65
Citations as of Dec 19, 2025
WEB OF SCIENCETM
Citations
59
Citations as of Dec 18, 2025
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



