Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours
In recent years, free-floating bike-sharing systems (FFBSSs) have been considerably developed in China. As there is no requirement to construct bike stations, this system can substantially reduce the cost when compared to the traditional bike-sharing systems. However, FFBSSs have also become a criti...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2019/4308509 |
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| author | Zhuo Sun Yiming Li Yi Zuo |
| author_facet | Zhuo Sun Yiming Li Yi Zuo |
| author_sort | Zhuo Sun |
| collection | DOAJ |
| description | In recent years, free-floating bike-sharing systems (FFBSSs) have been considerably developed in China. As there is no requirement to construct bike stations, this system can substantially reduce the cost when compared to the traditional bike-sharing systems. However, FFBSSs have also become a critical cause of parking disorder, especially during the morning and evening rush hours. To address this issue, the local governments stipulated that FFBSSs are required to deploy virtual stations near public transit stations and major establishments. Therefore, the location assignment of virtual stations is sufficiently considered in the FFBSSs, which is required to solve the parking disorder and satisfy the user demand, simultaneously. The purpose of this study is to optimize the location assignment of virtual stations that can meet the growing demand of users by analyzing the usage data of their shared bikes. This optimization problem is generally formulated as a mixed-integer linear programming (MILP) model to maximize the user demand. As an alternative solution, this article proposes a clustering algorithm, which can solve this problem in real time. The experimental results demonstrate that the MILP model and the proposed method are superior to the K-means method. Our method not only provides a solution for maximizing the user demand but also gives an optimized design scheme of the FFBSSs that represents the characteristics of virtual stations. |
| format | Article |
| id | doaj-art-8c7db63fba7f45f6b3c20468d3593787 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-8c7db63fba7f45f6b3c20468d35937872025-02-03T06:11:32ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/43085094308509Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush HoursZhuo Sun0Yiming Li1Yi Zuo2Transportation Engineering College, Dalian Maritime University, Dalian 116026, ChinaTransportation Engineering College, Dalian Maritime University, Dalian 116026, ChinaCollaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian 116026, ChinaIn recent years, free-floating bike-sharing systems (FFBSSs) have been considerably developed in China. As there is no requirement to construct bike stations, this system can substantially reduce the cost when compared to the traditional bike-sharing systems. However, FFBSSs have also become a critical cause of parking disorder, especially during the morning and evening rush hours. To address this issue, the local governments stipulated that FFBSSs are required to deploy virtual stations near public transit stations and major establishments. Therefore, the location assignment of virtual stations is sufficiently considered in the FFBSSs, which is required to solve the parking disorder and satisfy the user demand, simultaneously. The purpose of this study is to optimize the location assignment of virtual stations that can meet the growing demand of users by analyzing the usage data of their shared bikes. This optimization problem is generally formulated as a mixed-integer linear programming (MILP) model to maximize the user demand. As an alternative solution, this article proposes a clustering algorithm, which can solve this problem in real time. The experimental results demonstrate that the MILP model and the proposed method are superior to the K-means method. Our method not only provides a solution for maximizing the user demand but also gives an optimized design scheme of the FFBSSs that represents the characteristics of virtual stations.http://dx.doi.org/10.1155/2019/4308509 |
| spellingShingle | Zhuo Sun Yiming Li Yi Zuo Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours Journal of Advanced Transportation |
| title | Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours |
| title_full | Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours |
| title_fullStr | Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours |
| title_full_unstemmed | Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours |
| title_short | Optimizing the Location of Virtual Stations in Free-Floating Bike-Sharing Systems with the User Demand during Morning and Evening Rush Hours |
| title_sort | optimizing the location of virtual stations in free floating bike sharing systems with the user demand during morning and evening rush hours |
| url | http://dx.doi.org/10.1155/2019/4308509 |
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