Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91813
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
| dc.creator | Zhao, R | en_US |
| dc.creator | Liu, W | en_US |
| dc.creator | Zhang, F | en_US |
| dc.creator | Koo, TTR | en_US |
| dc.creator | Lodewijks, G | en_US |
| dc.date.accessioned | 2021-12-16T01:26:48Z | - |
| dc.date.available | 2021-12-16T01:26:48Z | - |
| dc.identifier.issn | 2168-0566 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/91813 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor & Francis | en_US |
| dc.rights | © 2021 Hong Kong Society for Transportation Studies Limited | en_US |
| dc.rights | This is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica B: Transport Dynamics on 30 Nov 2021 (Published online), available online: http://www.tandfonline.com/10.1080/21680566.2021.2008279 | en_US |
| dc.subject | Airport | en_US |
| dc.subject | Passenger ground transport | en_US |
| dc.subject | Shuttle service | en_US |
| dc.subject | Time–space network | en_US |
| dc.subject | Monte Carlo simulation | en_US |
| dc.title | Passenger shuttle service network design in an airport | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 1099 | en_US |
| dc.identifier.epage | 1125 | en_US |
| dc.identifier.volume | 10 | en_US |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.doi | 10.1080/21680566.2021.2008279 | en_US |
| dcterms.abstract | This study examines the service network design problem (SNDP) for passenger shuttle buses in the airport and nearby places (e.g. train stations, parking, hotels, shopping areas). A time–space service network for bus flows and time–space networks for passenger flows are developed. Based on proposed time–space networks, the studied SNDP is formulated as a mixed integer linear program (MILP) for a single-type bus fleet and deterministic passenger demand, where the objective is to minimize the weighted sum of passenger cost and service operating cost. We then extend the developed SNDP model to the heterogeneous multi-type bus fleet case and the stochastic demand case. To solve the stochastic demand case, a Monte Carlo simulation-based approach is adopted, which is further coupled with the ‘effective demand’ concept (mean demand value plus a margin). The proposed SNDP models and solution approach are applied on the inter-terminal transport network at Sydney Kingsford Smith Airport for illustration. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Transportmetrica. B, Transport dynamics, 2022, v. 10, no. 1, p. 1099-1125 | en_US |
| dcterms.isPartOf | Transportmetrica. B, Transport dynamics | en_US |
| dcterms.issued | 2022 | - |
| dc.identifier.scopus | 2-s2.0-85120378982 | - |
| dc.description.validate | 202112 bchy | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | a1107-n01, a1606 | - |
| dc.identifier.SubFormID | 43949, 45603 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | Australian Research Council (DE200101793), University of Hong Kong (202009185002) | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Zhao_Passenger_Shuttle_Service.pdf | Pre-Published version | 1.76 MB | Adobe PDF | View/Open |
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