Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand
System resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. This study innovatively introduces three types of invalid demand with negative effect including waiting, transfer, and abandoning, which consists of the total demand of bike-sha...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/8843783 |
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| _version_ | 1850163894665871360 |
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| author | Liu He Tangyi Guo Kun Tang |
| author_facet | Liu He Tangyi Guo Kun Tang |
| author_sort | Liu He |
| collection | DOAJ |
| description | System resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. This study innovatively introduces three types of invalid demand with negative effect including waiting, transfer, and abandoning, which consists of the total demand of bike-sharing system. Through exploring the dynamic relationship among users’ travel demands, the quantity and capacity of bikes at the rental points, the records of bicycles borrowed and returned, and the vehicle scheduling schemes, a demand forecasting model for bike-sharing is established. According to the predicted bikes and the maximum capacity limit at each rental point, an optimization model of scheduling scheme is proposed to reduce the invalid demand and the total scheduling time. A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). The proposed model is applied to a case study and the optimal solution set and corresponding Pareto front are obtained. The invalid demand is greatly reduced from 1094 to 26 by an effective scheduling of 3 rounds and 96 minutes. Empirical results show that the proposed model is able to optimize the resource allocation of bike-sharing, significantly reduce the invalid demand caused by the absence of bikes at the rental point such as waiting in a place, walking to other rental points, and giving up for other travel modes, and effectively improve the system service level. |
| format | Article |
| id | doaj-art-ed1529ca128940b3b77c7e65633f5a7d |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-ed1529ca128940b3b77c7e65633f5a7d2025-08-20T02:22:06ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/88437838843783Dynamic Scheduling Model of Bike-Sharing considering Invalid DemandLiu He0Tangyi Guo1Kun Tang2Department of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, ChinaDepartment of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, ChinaDepartment of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, ChinaSystem resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. This study innovatively introduces three types of invalid demand with negative effect including waiting, transfer, and abandoning, which consists of the total demand of bike-sharing system. Through exploring the dynamic relationship among users’ travel demands, the quantity and capacity of bikes at the rental points, the records of bicycles borrowed and returned, and the vehicle scheduling schemes, a demand forecasting model for bike-sharing is established. According to the predicted bikes and the maximum capacity limit at each rental point, an optimization model of scheduling scheme is proposed to reduce the invalid demand and the total scheduling time. A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). The proposed model is applied to a case study and the optimal solution set and corresponding Pareto front are obtained. The invalid demand is greatly reduced from 1094 to 26 by an effective scheduling of 3 rounds and 96 minutes. Empirical results show that the proposed model is able to optimize the resource allocation of bike-sharing, significantly reduce the invalid demand caused by the absence of bikes at the rental point such as waiting in a place, walking to other rental points, and giving up for other travel modes, and effectively improve the system service level.http://dx.doi.org/10.1155/2020/8843783 |
| spellingShingle | Liu He Tangyi Guo Kun Tang Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand Journal of Advanced Transportation |
| title | Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand |
| title_full | Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand |
| title_fullStr | Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand |
| title_full_unstemmed | Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand |
| title_short | Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand |
| title_sort | dynamic scheduling model of bike sharing considering invalid demand |
| url | http://dx.doi.org/10.1155/2020/8843783 |
| work_keys_str_mv | AT liuhe dynamicschedulingmodelofbikesharingconsideringinvaliddemand AT tangyiguo dynamicschedulingmodelofbikesharingconsideringinvaliddemand AT kuntang dynamicschedulingmodelofbikesharingconsideringinvaliddemand |