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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/40674
Title: A data-driven optimization computational tool design for bike-sharing station distribution in small to medium-sized cities: a case study for Cuenca, Ecuador
Authors: Cueva Vera, Wilson Fernando
Cedillo Orellana, Irene Priscila
Shi, Pengcheng
metadata.dc.ucuenca.correspondencia: Cueva Vera, Wilson Fernando, wfc497@rit.edu
Keywords: Pollutants
Bike sharing system
Optimization
Data-driven
Public bike system
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 2. Ingeniería y Tecnología
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 2.1.5 Ingeniería de Transporte
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 2.1 Ingeniería Civil
metadata.dc.ucuenca.areaconocimientounescoamplio: 07 - Ingeniería, Industria y Construcción
metadata.dc.ucuenca.areaconocimientounescodetallado: 0732 - Construcción e Ingeniería Civil
metadata.dc.ucuenca.areaconocimientounescoespecifico: 073 - Arquitectura y Construcción
Issue Date: 2022
metadata.dc.ucuenca.embargoend: 30-Nov-2050
metadata.dc.ucuenca.volumen: Volumen 55
metadata.dc.source: Lecture Notes in Information Systems and Organisation
metadata.dc.identifier.doi: 10.1007/978-3-030-95354-6_1
Publisher: Springer Science and Business Media Deutschland GmbH
metadata.dc.description.city: 
Valencia
metadata.dc.type: ARTÍCULO DE CONFERENCIA
Abstract: 
Faced with heavy vehicular traffic at present, the strategic implementation of Bike Sharing Systems (BSSs) in cities as an alternative means of transport for users is increasingly being adopted. These solutions reduce the environmental burden posed by other means of transportation, decrease costs for citizens, improves people's health due to physical activity, among other advantages. However, aspects such as the definition of bike stations’ locations represent a challenge when these solutions are being implemented. Therefore, this paper presents a software tool design that supports a method that defines the location and number of stations within a BSS. Also, the tool uses a data-driven optimization model to establish the location of stations. Finally, a case study carried out in Cuenca—Ecuador, demonstrates the proposal's feasibility, showing a significant concordance with the consulting firms-consortia results (70–90% of coincidence) at a lower cost
URI: http://dspace.ucuenca.edu.ec/handle/123456789/40674
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128718234&doi=10.1007%2f978-3-030-95354-6_1&partnerID=40&md5=e9bc014627f6d10f6437090dead67c44
metadata.dc.ucuenca.urifuente: https://www.springer.com/series/11237/books
ISBN: 978-303095353-9
ISSN: 2195-.4968
Appears in Collections:Artículos

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