Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes
Shared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2023-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/5702188 |
| _version_ | 1797855360488308736 |
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| author | Rong Zheng Hongtai Yang Lanzhen Jiang Jinghai Huo Xiaoqian Lu Malik Muneeb Abid |
| author_facet | Rong Zheng Hongtai Yang Lanzhen Jiang Jinghai Huo Xiaoqian Lu Malik Muneeb Abid |
| author_sort | Rong Zheng |
| collection | DOAJ |
| description | Shared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of the cleaning and disinfection scheme of the dockless shared bikes. The disinfection is assumed to be performed at night, when the usage is lowest. By regarding the disinfection staff as traveling salesmen, the model is formulated as an extension of the Multidepot Multiple Traveling Salesman Problem (MDMTSP). The objective function is to minimize the total cost; which consists of the cost associated with the working time and per-capita cost of the disinfection staff. A heuristic algorithm combining k-means clustering and genetic algorithm (K-GA) is adopted to find the lower bound solution. Then, the K-GA-adjustment algorithm has been adopted to find the solutions that satisfy the constraints. To reduce the computing time needed, an approximate function for the lower bound of the optimal number of disinfection staff is obtained by constructing a Continuous Approximation (CA) model. A case study based on real location data of shared bikes in Chengdu, China, is performed to show how the maintenance department could adopt the optimization framework to design an efficient scheme to clean and disinfect the shared bikes. |
| first_indexed | 2024-04-09T20:22:29Z |
| format | Article |
| id | doaj.art-c6d55321e91b436181b5cfb4327884cb |
| institution | Directory Open Access Journal |
| issn | 2042-3195 |
| language | English |
| last_indexed | 2024-04-09T20:22:29Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi-Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj.art-c6d55321e91b436181b5cfb4327884cb2023-03-31T00:00:03ZengHindawi-WileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/5702188Optimizing the Cleaning and Disinfection Scheme for Dockless Shared BikesRong Zheng0Hongtai Yang1Lanzhen Jiang2Jinghai Huo3Xiaoqian Lu4Malik Muneeb Abid5School of Transportation and LogisticsSchool of Transportation and LogisticsSchool of Transportation and LogisticsSchool of Transportation and LogisticsSchool of Transportation and LogisticsDepartment of Civil EngineeringShared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of the cleaning and disinfection scheme of the dockless shared bikes. The disinfection is assumed to be performed at night, when the usage is lowest. By regarding the disinfection staff as traveling salesmen, the model is formulated as an extension of the Multidepot Multiple Traveling Salesman Problem (MDMTSP). The objective function is to minimize the total cost; which consists of the cost associated with the working time and per-capita cost of the disinfection staff. A heuristic algorithm combining k-means clustering and genetic algorithm (K-GA) is adopted to find the lower bound solution. Then, the K-GA-adjustment algorithm has been adopted to find the solutions that satisfy the constraints. To reduce the computing time needed, an approximate function for the lower bound of the optimal number of disinfection staff is obtained by constructing a Continuous Approximation (CA) model. A case study based on real location data of shared bikes in Chengdu, China, is performed to show how the maintenance department could adopt the optimization framework to design an efficient scheme to clean and disinfect the shared bikes.http://dx.doi.org/10.1155/2023/5702188 |
| spellingShingle | Rong Zheng Hongtai Yang Lanzhen Jiang Jinghai Huo Xiaoqian Lu Malik Muneeb Abid Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes Journal of Advanced Transportation |
| title | Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes |
| title_full | Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes |
| title_fullStr | Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes |
| title_full_unstemmed | Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes |
| title_short | Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes |
| title_sort | optimizing the cleaning and disinfection scheme for dockless shared bikes |
| url | http://dx.doi.org/10.1155/2023/5702188 |
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