On-line dynamic station redeployments in bike-sharing systems

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dc.contributor.authorManna, Carlo
dc.contributor.editorAdorni, Giovanni
dc.contributor.editorCagnoni, Stefano
dc.contributor.editorGori, Marco
dc.contributor.editorMaratea, Marco
dc.date.accessioned2017-02-01T09:23:08Z
dc.date.available2017-02-01T09:23:08Z
dc.date.issued2016-11-05
dc.date.updated2017-01-31T12:14:19Z
dc.description.abstractBike-sharing has seen great development during recent years, both in Europe and globally. However, these systems are far from perfect. The uncertainty of the customer demand often leads to an unbalanced distribution of bicycles over the time and space (congestion and/or starvation), resulting both in a loss of customers and a poor customer experience. In order to improve those aspects, we propose a dynamic bike-sharing system, which combines the standard fixed base stations with movable stations (using trucks), which will able to be dynamically re-allocated according to the upcoming forecasted customer demand during the day in real-time. The purpose of this paper is to investigate whether using moveable stations in designing the bike-sharing system has a significant positive effect on the system performance. To that end, we contribute an on-line stochastic optimization formulation to address the redeployment of the moveable stations during the day, to better match the upcoming customer demand. Finally, we demonstrate the utility of our approach with numerical experiments using data provided by bike-sharing companies.en
dc.description.statusNot peer revieweden
dc.description.urihttp://www.aixia2016.unige.it/en
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationManna C. (2016) ‘On-line dynamic station redeployments in bike-sharing systems’, in Adorni G., Cagnoni S., Gori M. and Maratea M. (eds.) AI*IA 2016 Advances in Artificial Intelligence. AI*IA 2016: XVth International Conference of the Italian Association for Artificial Intelligence, Genova, Italy, 29 November –1 December. Lecture Notes in Computer Science, Vol. 10037. Springer International Publishing AG. doi:10.1007/978-3-319-49130-1_2en
dc.identifier.doi10.1007/978-3-319-49130-1_2
dc.identifier.endpage25en
dc.identifier.issn0302-9743
dc.identifier.journaltitleLecture Notes in Computer Scienceen
dc.identifier.startpage13en
dc.identifier.urihttps://hdl.handle.net/10468/3548
dc.identifier.volume10037en
dc.language.isoenen
dc.publisherSpringer International Publishing AGen
dc.relation.ispartofAI*IA 2016 Advances in Artificial Intelligence: XVth International Conference of the Italian Association for Artificial Intelligence
dc.relation.ispartofLecture Notes in Computer Science
dc.relation.urihttp://link.springer.com/book/10.1007/978-3-319-49130-1
dc.rights© 2016, Springer International Publishing AG. The final publication is available at http://link.springer.com/chapter/10.1007%2F978-3-319-49130-1_2en
dc.subjectOn-line combinatorial optimizationen
dc.subjectUncertaintyen
dc.subjectSmart citiesen
dc.titleOn-line dynamic station redeployments in bike-sharing systemsen
dc.typeConference itemen
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