| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Logistics and Maritime Studies | en_US |
| dc.creator | Xu, X | en_US |
| dc.creator | Li, CL | en_US |
| dc.creator | Xu, Z | en_US |
| dc.date.accessioned | 2021-08-04T01:52:03Z | - |
| dc.date.available | 2021-08-04T01:52:03Z | - |
| dc.identifier.issn | 0191-2615 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/90597 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Pergamon Press | en_US |
| dc.subject | Dynamic passenger demand | en_US |
| dc.subject | Lagrangian relaxation | en_US |
| dc.subject | Platform assignment | en_US |
| dc.subject | Stop-skipping | en_US |
| dc.subject | Train timetabling | en_US |
| dc.title | Train timetabling with stop-skipping, passenger flow, and platform choice considerations | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 52 | en_US |
| dc.identifier.epage | 74 | en_US |
| dc.identifier.volume | 150 | en_US |
| dc.identifier.doi | 10.1016/j.trb.2021.06.001 | en_US |
| dcterms.abstract | In conventional railway planning processes, stop-skipping decisions are often made at the line planning stage, which is executed prior to train timetabling and platform assignment. However, stop-skipping can shorten passenger journey time and also save on train operating costs. Hence, integrating train timetabling, stop-skipping, and platform choice decisions can help generate train timetables with improved passenger convenience and higher train operating efficiency. Integrating these decisions is a challenging task, as these decisions affect passenger train transfer behavior, which in turn affects the entire passenger flow. This study is a first attempt at integrating these decisions while simultaneously taking into account the passenger flow. We consider a train timetabling problem on a single, one-way track with stop-skipping, platform choice, and passenger flow considerations, and we formulate it as a constrained minimum-cost multi-commodity network flow problem on a time–space network. We analyze the problem's complexity and develop a Lagrangian relaxation heuristic to solve the problem. We conduct a computational study with randomly generated data that captures the characteristics of the Beijing–Shanghai high-speed railway line. The computational results report the effectiveness of our Lagrangian relaxation heuristic and how the railway's service capacity and passenger traffic intensity affect the solution. | en_US |
| dcterms.accessRights | embargoed access | en_US |
| dcterms.bibliographicCitation | Transportation research. Part B, Methodological, Aug. 2021, v. 150, p. 52-74 | en_US |
| dcterms.isPartOf | Transportation research. Part B, Methodological | en_US |
| dcterms.issued | 2021-08 | - |
| dc.identifier.scopus | 2-s2.0-85108082344 | - |
| dc.identifier.eissn | 1879-2367 | en_US |
| dc.description.validate | 202108 bcvc | en_US |
| dc.description.oa | Not applicable | en_US |
| dc.identifier.FolderNumber | a0986-n03 | - |
| dc.identifier.SubFormID | 2347 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingText | T32-101/15-R | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.date.embargo | 2023.08.31 | en_US |
| Appears in Collections: | Journal/Magazine Article | |
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