Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study
Carsharing is regarded as a new mode of transportation that can meet the diversity of travel demands. Carsharing systems have different operating modes, and one-way systems are more widely used since cars can be dropped off at any station. However, their planning involves a series of joint decisions...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/6142950 |
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| _version_ | 1832565565321904128 |
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| author | Yongjun Chen Lulin Wang Jingjing Tian |
| author_facet | Yongjun Chen Lulin Wang Jingjing Tian |
| author_sort | Yongjun Chen |
| collection | DOAJ |
| description | Carsharing is regarded as a new mode of transportation that can meet the diversity of travel demands. Carsharing systems have different operating modes, and one-way systems are more widely used since cars can be dropped off at any station. However, their planning involves a series of joint decisions regarding the number, size, and location of stations, as well as the fleet size. This paper develops a data-driven mixed-integer linear programming (MILP) model for planning one-way carsharing systems that consider the spatial distribution of demand and the interacting decisions between stations. The characteristics of existing stations and their spatiotemporal correlations are an important part of the model. To solve the MILP model, the extension of the Benders decomposition algorithm is adopted. The practicality of the proposed approach is demonstrated in a case study in Beijing, China. The results show that the existing planning of carsharing could result in a serious waste of resources. In contrast, the proposed method can obtain effective results in a reasonable time. The location results corresponding to a different rate of satisfied demand show that increasing the parking spots to improve the interaction between stations can effectively reduce the cost of operations. It should be noted that this paper only considers the benefit of operators. Future works will be carried out to optimize the one-way carsharing system by considering the benefits of operators, as well as the benefits of users and society. In addition, the impact of COVID-19 will be taken into account in future modeling and case studies. |
| format | Article |
| id | doaj-art-2202dde710af41d7aadae6a11ad8be3b |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-2202dde710af41d7aadae6a11ad8be3b2025-02-03T01:07:12ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/6142950Station Location Optimization for the One-Way Carsharing System: Modeling and a Case StudyYongjun Chen0Lulin Wang1Jingjing Tian2School of Urban Economics and ManagementSchool of Urban Economics and ManagementSchool of Traffic and TransportationCarsharing is regarded as a new mode of transportation that can meet the diversity of travel demands. Carsharing systems have different operating modes, and one-way systems are more widely used since cars can be dropped off at any station. However, their planning involves a series of joint decisions regarding the number, size, and location of stations, as well as the fleet size. This paper develops a data-driven mixed-integer linear programming (MILP) model for planning one-way carsharing systems that consider the spatial distribution of demand and the interacting decisions between stations. The characteristics of existing stations and their spatiotemporal correlations are an important part of the model. To solve the MILP model, the extension of the Benders decomposition algorithm is adopted. The practicality of the proposed approach is demonstrated in a case study in Beijing, China. The results show that the existing planning of carsharing could result in a serious waste of resources. In contrast, the proposed method can obtain effective results in a reasonable time. The location results corresponding to a different rate of satisfied demand show that increasing the parking spots to improve the interaction between stations can effectively reduce the cost of operations. It should be noted that this paper only considers the benefit of operators. Future works will be carried out to optimize the one-way carsharing system by considering the benefits of operators, as well as the benefits of users and society. In addition, the impact of COVID-19 will be taken into account in future modeling and case studies.http://dx.doi.org/10.1155/2022/6142950 |
| spellingShingle | Yongjun Chen Lulin Wang Jingjing Tian Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study Journal of Advanced Transportation |
| title | Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study |
| title_full | Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study |
| title_fullStr | Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study |
| title_full_unstemmed | Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study |
| title_short | Station Location Optimization for the One-Way Carsharing System: Modeling and a Case Study |
| title_sort | station location optimization for the one way carsharing system modeling and a case study |
| url | http://dx.doi.org/10.1155/2022/6142950 |
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