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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/39095
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: Shi, Pengcheng
Cueva Vera, Wilson Fernando
Cedillo Orellana, Irene Priscila
metadata.dc.ucuenca.correspondencia: Cueva Vera, Wilson Fernando, wfc9474@rit.edu
Keywords: Datadriven
Bike sharing system
Public bike system
Optimization
Pollutants
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 1. Ciencias Naturales y Exactas
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 1.2.1 Ciencias de la Computación
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 1.2 Informática y Ciencias de la Información
metadata.dc.ucuenca.areaconocimientounescoamplio: 06 - Información y Comunicación (TIC)
metadata.dc.ucuenca.areaconocimientounescodetallado: 0613 - Software y Desarrollo y Análisis de Aplicativos
metadata.dc.ucuenca.areaconocimientounescoespecifico: 061 - Información y Comunicación (TIC)
Issue Date: 2022
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
Publisher: Springer Nature Switzerland AG
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 firmsconsortia results (70-90% of coincidence) at a lower cost.
URI: http://dspace.ucuenca.edu.ec/handle/123456789/39095
https://link.springer.com/chapter/10.1007/978-3-030-95354-6_1
metadata.dc.ucuenca.urifuente: https://link.springer.com/book/10.1007/978-3-030-95354-6
ISBN: 978-3-030-95353-9 , 978-3-030-95354-6 (eBook)
ISSN: 2195-4968, e 2195-4976
Appears in Collections:Artículos

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