Evolutionary algorithm for vehicle routing for shared e-bicycle battery replacement and recycling Article Swipe
Yu‐Jun Zheng
,
Xin Chen
,
Hong-Fang Yan
,
Minxia Zhang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.asoc.2023.110023
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.asoc.2023.110023
Shared electric bicycles (e-bicycles) are becoming an increasingly popular model of sharing economy that provides the public with a convenient and labor-saving transport alternative. Efficient battery replacement is critical to maintain the operational capability of e-bicycles, but is quite difficult as there are often a large number of e-bicycles that are widely dispersed. In this paper, we study a problem of scheduling multiple vehicles to deliver fully-charged batteries to and take back low-power batteries from shared e-bicycles scattered in numerous parking spots, while the low-power batteries are recharged in battery depots for potential re-utilization. The aim of this problem is to minimize the completion time of all battery replacement tasks so as to keep a high operational efficiency of the system. The problem differs from existing vehicle routing problems in two main special features: (1) equivalent exchange of fully-charged batteries and low-power batteries; (2) recycling of batteries. To efficiently solve this special problem, we propose an evolutionary algorithm using variable local-search-based mutation to balance global exploration and local exploitation and employing enhanced local search around each newly found best known solution to improve accuracy. Experiments on test instances and real-world instances demonstrate the competitive performance of the proposed method.
Related Topics
Concepts
Computer science
Battery (electricity)
Scheduling (production processes)
Vehicle routing problem
Job shop scheduling
Evolutionary algorithm
Power (physics)
Routing (electronic design automation)
Electric vehicle
Mathematical optimization
Embedded system
Machine learning
Physics
Quantum mechanics
Mathematics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.asoc.2023.110023
- OA Status
- hybrid
- Cited By
- 14
- References
- 74
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4320525591Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.asoc.2023.110023Digital Object Identifier
- Title
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Evolutionary algorithm for vehicle routing for shared e-bicycle battery replacement and recyclingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-18Full publication date if available
- Authors
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Yu‐Jun Zheng, Xin Chen, Hong-Fang Yan, Minxia ZhangList of authors in order
- Landing page
-
https://doi.org/10.1016/j.asoc.2023.110023Publisher landing page
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.asoc.2023.110023Direct OA link when available
- Concepts
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Computer science, Battery (electricity), Scheduling (production processes), Vehicle routing problem, Job shop scheduling, Evolutionary algorithm, Power (physics), Routing (electronic design automation), Electric vehicle, Mathematical optimization, Embedded system, Machine learning, Physics, Quantum mechanics, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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14Total citation count in OpenAlex
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2025: 4, 2024: 7, 2023: 3Per-year citation counts (last 5 years)
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74Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| publication_date | 2023-01-18 |
| publication_year | 2023 |
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