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A Systematic Review of Station Location Techniques for Bicycle-Sharing Systems Planning and Operation

Journal

Publisher

MDPI
DOI: 10.3390/ijgi10080554

Keywords

bike-sharing systems; station location; GIS; optimization problem; MCDM; location criteria classification

Funding

  1. Thales Group in Portugal [4853]

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Designing or expanding a bicycle-sharing system involves addressing the infrastructure's location of the bicycle stations, which is crucial for system operation. Geographic information systems (GIS) can support decision-making in this context. Recent research has focused on categorizing and improving location modeling techniques for bike stations, with a particular emphasis on the use of GIS and multi-criteria decision making (MCDM) to optimize system performance.
Designing or expanding a bicycle-sharing system (BSS) involves addressing the infrastructure's location of the bicycle stations. Station location is an essential factor for designing and implementing a new system or for its operation. In a complex spatial optimization context, geographic information systems (GIS) can support this decision problem. There are also numerous ways of subdividing the broad spectrum of location-allocation models used in previous studies. However, a station location comprehensive review and systematization with the specific aim of characterizing the state of the art of BSS is missing. The present research aimed to provide a comprehensive systematization for station location problems, criteria, and techniques, seeking to identify the current state of practice. We searched scientific publication databases to collect relevant publications-the final list comprised 24 papers for the literature review. The systematization addresses the two major problems concerning bicycle station location: initial network design and operation improvement (where changes in operating a BSS are implemented). Based on the literature, we propose a set of four main criteria for choosing appropriate places for bike stations (or parking) in a city: bike network, operator, user, and city infrastructure. The sub-criteria mentioned in the literature are categorized based on the proposed classification and new sub-criteria are suggested. We also group location modeling techniques into three categories: mathematical algorithms, multi-criteria decision making, and GIS. Combining GIS and multi-criteria decision making (MCDM) has received more attention in recent years to locate bike stations, evaluate their operating performance, and have more accurate and practical results.

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