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Article: An enhanced artificial bee colony algorithm for the green bike repositioning problem with broken bikes
Title | An enhanced artificial bee colony algorithm for the green bike repositioning problem with broken bikes |
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Authors | |
Keywords | Green bike repositioning problem Emissions Broken bikes Artificial bee colony algorithm |
Issue Date | 2021 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/trc |
Citation | Transportation Research Part C: Emerging Technologies, 2021, v. 125, p. article no. 102895 How to Cite? |
Abstract | The Bike Repositioning Problem (BRP) has raised many researchers’ attention in recent years to improve the service quality of Bike Sharing Systems (BSSs). It is mainly about designing the routes and loading instructions for the vehicles to transfer bikes among stations in order to achieve a desirable state. This study tackles a static green BRP that aims to minimize the CO2 emissions of the repositioning vehicle besides achieving the target inventory level at stations as much as possible within the time budget. Two types of bikes are considered, including usable and broken bikes. The Enhanced Artificial Bee Colony (EABC) algorithm is adopted to generate the vehicle route. Two methods, namely heuristic and exact methods, are proposed and incorporated into the EABC algorithm to compute the loading/unloading quantities at each stop. Computational experiments were conducted on the real-world instances having 10–300 stations. The results indicate that the proposed solution methodology that relies on the heuristic loading method can provide optimal solutions for small instances. For large-scale instances, it can produce better feasible solutions than two benchmark methodologies in the literature. |
Persistent Identifier | http://hdl.handle.net/10722/307846 |
ISSN | 2023 Impact Factor: 7.6 2023 SCImago Journal Rankings: 2.860 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wang, Y | - |
dc.contributor.author | Szeto, WY | - |
dc.date.accessioned | 2021-11-12T13:38:45Z | - |
dc.date.available | 2021-11-12T13:38:45Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Transportation Research Part C: Emerging Technologies, 2021, v. 125, p. article no. 102895 | - |
dc.identifier.issn | 0968-090X | - |
dc.identifier.uri | http://hdl.handle.net/10722/307846 | - |
dc.description.abstract | The Bike Repositioning Problem (BRP) has raised many researchers’ attention in recent years to improve the service quality of Bike Sharing Systems (BSSs). It is mainly about designing the routes and loading instructions for the vehicles to transfer bikes among stations in order to achieve a desirable state. This study tackles a static green BRP that aims to minimize the CO2 emissions of the repositioning vehicle besides achieving the target inventory level at stations as much as possible within the time budget. Two types of bikes are considered, including usable and broken bikes. The Enhanced Artificial Bee Colony (EABC) algorithm is adopted to generate the vehicle route. Two methods, namely heuristic and exact methods, are proposed and incorporated into the EABC algorithm to compute the loading/unloading quantities at each stop. Computational experiments were conducted on the real-world instances having 10–300 stations. The results indicate that the proposed solution methodology that relies on the heuristic loading method can provide optimal solutions for small instances. For large-scale instances, it can produce better feasible solutions than two benchmark methodologies in the literature. | - |
dc.language | eng | - |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/trc | - |
dc.relation.ispartof | Transportation Research Part C: Emerging Technologies | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Green bike repositioning problem | - |
dc.subject | Emissions | - |
dc.subject | Broken bikes | - |
dc.subject | Artificial bee colony algorithm | - |
dc.title | An enhanced artificial bee colony algorithm for the green bike repositioning problem with broken bikes | - |
dc.type | Article | - |
dc.identifier.email | Szeto, WY: ceszeto@hku.hk | - |
dc.identifier.authority | Szeto, WY=rp01377 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1016/j.trc.2020.102895 | - |
dc.identifier.scopus | eid_2-s2.0-85102032396 | - |
dc.identifier.hkuros | 329299 | - |
dc.identifier.volume | 125 | - |
dc.identifier.spage | article no. 102895 | - |
dc.identifier.epage | article no. 102895 | - |
dc.identifier.isi | WOS:000636094000015 | - |
dc.publisher.place | United Kingdom | - |