Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail
Traveling by bike-sharing systems has become an indispensable means of transportation in our daily lives because green commuting has gradually become a consensus and conscious action. However, the problem of “difficult to rent or to return a bike” has gradually become an issue in operating the bike-...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/3790888 |
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| _version_ | 1850156929052049408 |
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| author | Zhenghua Hu Kejie Huang Enyou Zhang Qi’ang Ge Xiaoxue Yang |
| author_facet | Zhenghua Hu Kejie Huang Enyou Zhang Qi’ang Ge Xiaoxue Yang |
| author_sort | Zhenghua Hu |
| collection | DOAJ |
| description | Traveling by bike-sharing systems has become an indispensable means of transportation in our daily lives because green commuting has gradually become a consensus and conscious action. However, the problem of “difficult to rent or to return a bike” has gradually become an issue in operating the bike-sharing system. Moreover, scientific and systematic schemes that can efficiently complete the task of rebalancing bike-sharing systems are lacking. This study aims to introduce the basic idea of the k-divisive hierarchical clustering algorithm. A rebalancing strategy based on the model of level of detail in combination with genetic algorithm was proposed. Data were collected from the bike-sharing system in Ningbo. Results showed that the proposed algorithm could alleviate the problem of the uneven distribution of the demand for renting or returning bikes and effectively improve the service from the bike-sharing system. Compared with the traditional method, this algorithm helps reduce the effective time for rebalancing bike-sharing systems by 28.3%. Therefore, it is an effective rebalancing scheme. |
| format | Article |
| id | doaj-art-32cd5d918e09447c903567cd44879f9a |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-32cd5d918e09447c903567cd44879f9a2025-08-20T02:24:19ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/37908883790888Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of DetailZhenghua Hu0Kejie Huang1Enyou Zhang2Qi’ang Ge3Xiaoxue Yang4College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, ChinaCollege of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, ChinaNingbo Jianan Electronics Co., Ltd, Cixi, ChinaSchool of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, ChinaSchool of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, ChinaTraveling by bike-sharing systems has become an indispensable means of transportation in our daily lives because green commuting has gradually become a consensus and conscious action. However, the problem of “difficult to rent or to return a bike” has gradually become an issue in operating the bike-sharing system. Moreover, scientific and systematic schemes that can efficiently complete the task of rebalancing bike-sharing systems are lacking. This study aims to introduce the basic idea of the k-divisive hierarchical clustering algorithm. A rebalancing strategy based on the model of level of detail in combination with genetic algorithm was proposed. Data were collected from the bike-sharing system in Ningbo. Results showed that the proposed algorithm could alleviate the problem of the uneven distribution of the demand for renting or returning bikes and effectively improve the service from the bike-sharing system. Compared with the traditional method, this algorithm helps reduce the effective time for rebalancing bike-sharing systems by 28.3%. Therefore, it is an effective rebalancing scheme.http://dx.doi.org/10.1155/2021/3790888 |
| spellingShingle | Zhenghua Hu Kejie Huang Enyou Zhang Qi’ang Ge Xiaoxue Yang Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail Journal of Advanced Transportation |
| title | Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail |
| title_full | Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail |
| title_fullStr | Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail |
| title_full_unstemmed | Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail |
| title_short | Rebalancing Strategy for Bike-Sharing Systems Based on the Model of Level of Detail |
| title_sort | rebalancing strategy for bike sharing systems based on the model of level of detail |
| url | http://dx.doi.org/10.1155/2021/3790888 |
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